Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice.

PubMed

Bruno, D L; Ganesamoorthy, D; Schoumans, J; Bankier, A; Coman, D; Delatycki, M; Gardner, R J M; Hunter, M; James, P A; Kannu, P; McGillivray, G; Pachter, N; Peters, H; Rieubland, C; Savarirayan, R; Scheffer, I E; Sheffield, L; Tan, T; White, S M; Yeung, A; Bowman, Z; Ngo, C; Choy, K W; Cacheux, V; Wong, L; Amor, D J; Slater, H R

2009-02-01

Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

Mothers' appreciation of chromosomal microarray analysis for autism spectrum disorder.

PubMed

Giarelli, Ellen; Reiff, Marian

2015-10-01

The aim of this study was to examine mothers' experiences with chromosomal microarray analysis (CMA) for a child with autism spectrum disorder (ASD). This is a descriptive qualitative study using thematic content analysis of in-depth interview with 48 mothers of children who had genetic testing for ASD. The principal theme, "something is missing," included missing knowledge about genetics, information on use of the results, explanations of the relevance to the diagnosis, and relevance to life-long care. Two subordinate themes were (a) disappreciation of the helpfulness of scientific information to explain the diagnosis, and (b) returning to personal experience for interpretation. The test "appreciated" in value when results could be linked to the phenotype. © 2015, Wiley Periodicals, Inc.

Using phenotype microarrays in the assessment of the antibiotic susceptibility profile of bacteria isolated from wastewater in on-site treatment facilities.

PubMed

Jałowiecki, Łukasz; Chojniak, Joanna; Dorgeloh, Elmar; Hegedusova, Berta; Ejhed, Helene; Magnér, Jörgen; Płaza, Grażyna

2017-11-01

The scope of the study was to apply Phenotype Biolog MicroArray (PM) technology to test the antibiotic sensitivity of the bacterial strains isolated from on-site wastewater treatment facilities. In the first step of the study, the percentage values of resistant bacteria from total heterotrophic bacteria growing on solid media supplemented with various antibiotics were determined. In the untreated wastewater, the average shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria were 53, 56, and 42%, respectively. Meanwhile, the shares of kanamycin-, streptomycin-, and tetracycline-resistant bacteria in the treated wastewater were 39, 33, and 29%, respectively. To evaluate the antibiotic susceptibility of the bacteria present in the wastewater, using the phenotype microarrays (PMs), the most common isolates from the treated wastewater were chosen: Serratia marcescens ss marcescens, Pseudomonas fluorescens, Stenotrophomonas maltophilia, Stenotrophomonas rhizophila, Microbacterium flavescens, Alcaligenes faecalis ss faecalis, Flavobacterium hydatis, Variovorax paradoxus, Acinetobacter johnsonii, and Aeromonas bestiarum. The strains were classified as multi-antibiotic-resistant bacteria. Most of them were resistant to more than 30 antibiotics from various chemical classes. Phenotype microarrays could be successfully used as an additional tool for evaluation of the multi-antibiotic resistance of environmental bacteria and in preliminary determination of the range of inhibition concentration.

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Phenotypic Profiling of Scedosporium aurantiacum, an Opportunistic Pathogen Colonizing Human Lungs

PubMed Central

Kaur, Jashanpreet; Duan, Shu Yao; Vaas, Lea A. I.; Penesyan, Anahit; Meyer, Wieland; Paulsen, Ian T.; Nevalainen, Helena

2015-01-01

Genotyping studies of Australian Scedosporium isolates have revealed the strong prevalence of a recently described species: Scedosporium aurantiacum. In addition to occurring in the environment, this fungus is also known to colonise the respiratory tracts of cystic fibrosis (CF) patients. A high throughput Phenotype Microarray (PM) analysis using 94 assorted substrates (sugars, amino acids, hexose-acids and carboxylic acids) was carried out for four isolates exhibiting different levels of virulence, determined using a Galleria mellonella infection model. A significant difference was observed in the substrate utilisation patterns of strains displaying differential virulence. For example, certain sugars such as sucrose (saccharose) were utilised only by low virulence strains whereas some sugar derivatives such as D-turanose promoted respiration only in the more virulent strains. Strains with a higher level of virulence also displayed flexibility and metabolic adaptability at two different temperature conditions tested (28 and 37°C). Phenotype microarray data were integrated with the whole-genome sequence data of S. aurantiacum to reconstruct a pathway map for the metabolism of selected substrates to further elucidate differences between the strains. PMID:25811884

Phenotypic profiling of Scedosporium aurantiacum, an opportunistic pathogen colonizing human lungs.

PubMed

Kaur, Jashanpreet; Duan, Shu Yao; Vaas, Lea A I; Penesyan, Anahit; Meyer, Wieland; Paulsen, Ian T; Nevalainen, Helena

2015-01-01

Genotyping studies of Australian Scedosporium isolates have revealed the strong prevalence of a recently described species: Scedosporium aurantiacum. In addition to occurring in the environment, this fungus is also known to colonise the respiratory tracts of cystic fibrosis (CF) patients. A high throughput Phenotype Microarray (PM) analysis using 94 assorted substrates (sugars, amino acids, hexose-acids and carboxylic acids) was carried out for four isolates exhibiting different levels of virulence, determined using a Galleria mellonella infection model. A significant difference was observed in the substrate utilisation patterns of strains displaying differential virulence. For example, certain sugars such as sucrose (saccharose) were utilised only by low virulence strains whereas some sugar derivatives such as D-turanose promoted respiration only in the more virulent strains. Strains with a higher level of virulence also displayed flexibility and metabolic adaptability at two different temperature conditions tested (28 and 37°C). Phenotype microarray data were integrated with the whole-genome sequence data of S. aurantiacum to reconstruct a pathway map for the metabolism of selected substrates to further elucidate differences between the strains.

Nablus mask-like facial syndrome: deletion of chromosome 8q22.1 is necessary but not sufficient to cause the phenotype.

PubMed

Allanson, Judith; Smith, Amanda; Hare, Heather; Albrecht, Beate; Bijlsma, Emilia; Dallapiccola, Bruno; Donti, Emilio; Fitzpatrick, David; Isidor, Bertrand; Lachlan, Katherine; Le Caignec, Cedric; Prontera, Paolo; Raas-Rothschild, Annick; Rogaia, Daniela; van Bon, Bregje; Aradhya, Swaroop; Crocker, Susan F; Jarinova, Olga; McGowan-Jordan, Jean; Boycott, Kym; Bulman, Dennis; Fagerberg, Christina Ringmann

2012-09-01

Nablus mask-like facial syndrome (NMLFS) has many distinctive phenotypic features, particularly tight glistening skin with reduced facial expression, blepharophimosis, telecanthus, bulky nasal tip, abnormal external ear architecture, upswept frontal hairline, and sparse eyebrows. Over the last few years, several individuals with NMLFS have been reported to have a microdeletion of 8q21.3q22.1, demonstrated by microarray analysis. The minimal overlapping region is 93.98-96.22 Mb (hg19). Here we present clinical and microarray data from five singletons and two mother-child pairs who have heterozygous deletions significantly overlapping the region associated with NMLFS. Notably, while one mother and child were said to have mild tightening of facial skin, none of these individuals exhibited reduced facial expression or the classical facial phenotype of NMLFS. These findings indicate that deletion of the 8q21.3q22.1 region is necessary but not sufficient for development of the NMLFS. We discuss possible genetic mechanisms underlying the complex pattern of inheritance for this condition. Copyright © 2012 Wiley Periodicals, Inc.

Custom microarray construction and analysis for determining potential biomarkers of subchronic androgen exposure in the Eastern Mosquitofish (Gambusia holbrooki)

USGS Publications Warehouse

Brockmeier, Erica K.; Yu, Fahong; Amador, David Moraga; Bargar, Timothy A.; Denslow, Nancy D.

2013-01-01

Coupling microarray data with phenotypic changes driven by androgen exposure in mosquitofish is key for developing this organism into a bioindicator for EDCs. Future studies using this array will enhance knowledge of the biology and toxicological response of this species. This work provides a foundation of molecular knowledge and tools that can be used to delve further into understanding the biology of G. holbrooki and how this organism can be used as a bioindicator organism for endocrine disrupting pollutants in the environment.

Chromosomal microarray analysis in developmental delay and intellectual disability with comorbid conditions.

PubMed

Fan, Yanjie; Wu, Yanming; Wang, Lili; Wang, Yu; Gong, Zhuwen; Qiu, Wenjuan; Wang, Jingmin; Zhang, Huiwen; Ji, Xing; Ye, Jun; Han, Lianshu; Jin, Xingming; Shen, Yongnian; Li, Fei; Xiao, Bing; Liang, Lili; Zhang, Xia; Liu, Xiaomin; Gu, Xuefan; Yu, Yongguo

2018-05-24

Developmental delay (DD) and intellectual disability (ID) are frequently associated with a broad spectrum of additional phenotypes. Chromosomal microarray analysis (CMA) has been recommended as a first-tier test for DD/ID in general, whereas the diagnostic yield differs significantly among DD/ID patients with different comorbid conditions. To investigate the genotype-phenotype correlation, we examined the characteristics of identified pathogenic copy number variations (pCNVs) and compared the diagnostic yields among patient subgroups with different co-occurring conditions. This study is a retrospective review of CMA results generated from a mixed cohort of 710 Chinese patients with DD/ID. A total of 247 pCNVs were identified in 201 patients (28%). A large portion of these pCNVs were copy number losses, and the size of copy number losses was generally smaller than gains. The diagnostic yields were significantly higher in subgroups with co-occurring congenital heart defects (55%), facial dysmorphism (39%), microcephaly (34%) or hypotonia (35%), whereas co-occurring conditions of skeletal malformation (26%), brain malformation (24%) or epilepsy (24%) did not alter the yield. In addition, the diagnostic yield nominally correlated with ID severity. Varied yields exist in DD/ID patients with different phenotypic presentation. The presence of comorbid conditions can be among factors to consider when planning CMA.

Microarray-based mutation detection and phenotypic characterization in Korean patients with retinitis pigmentosa

PubMed Central

Kim, Cinoo; Kim, Kwang Joong; Bok, Jeong; Lee, Eun-Ju; Kim, Dong-Joon; Oh, Ji Hee; Park, Sung Pyo; Shin, Joo Young; Lee, Jong-Young

2012-01-01

Purpose To evaluate microarray-based genotyping technology for the detection of mutations responsible for retinitis pigmentosa (RP) and to perform phenotypic characterization of patients with pathogenic mutations. Methods DNA from 336 patients with RP and 360 controls was analyzed using the GoldenGate assay with microbeads containing 95 previously reported disease-associated mutations from 28 RP genes. Mutations identified by microarray-based genotyping were confirmed by direct sequencing. Segregation analysis and phenotypic characterization were performed in patients with mutations. The disease severity was assessed by visual acuity, electroretinography, optical coherence tomography, and kinetic perimetry. Results Ten RP-related mutations of five RP genes (PRP3 pre-mRNA processing factor 3 homolog [PRPF3], rhodopsin [RHO], phosphodiesterase 6B [PDE6B], peripherin 2 [PRPH2], and retinitis pigmentosa 1 [RP1]) were identified in 26 of the 336 patients (7.7%) and in six of the 360 controls (1.7%). The p.H557Y mutation in PDE6B, which was homozygous in four patients and heterozygous in nine patients, was the most frequent mutation (2.5%). Mutation segregation was assessed in four families. Among the patients with missense mutations, the most severe phenotype occurred in patients with p.D984G in RP1; less severe phenotypes occurred in patients with p.R135W in RHO; a relatively moderate phenotype occurred in patients with p.T494M in PRPF3, p.H557Y in PDE6B, or p.W316G in PRPH2; and a mild phenotype was seen in a patient with p.D190N in RHO. Conclusions The results reveal that the GoldenGate assay may not be an efficient method for molecular diagnosis in RP patients with rare mutations, although it has proven to be reliable and efficient for high-throughput genotyping of single-nucleotide polymorphisms. The clinical features varied according to the mutations. Continuous effort to identify novel RP genes and mutations in a population is needed to improve the efficiency and accuracy of the genetic diagnosis of RP. PMID:23049240

Classifying compound mechanism of action for linking whole cell phenotypes to molecular targets

PubMed Central

Bourne, Christina R.; Wakeham, Nancy; Bunce, Richard A.; Berlin, K. Darrell; Barrow, William W.

2013-01-01

Drug development programs have proven successful when performed at a whole cell level, thus incorporating solubility and permeability into the primary screen. However, linking those results to the target within the cell has been a major set-back. The Phenotype Microarray system, marketed and sold by Biolog, seeks to address this need by assessing the phenotype in combination with a variety of chemicals with known mechanism of action (MOA). We have evaluated this system for usefulness in deducing the MOA for three test compounds. To achieve this, we constructed a database with 21 known antimicrobials, which served as a comparison for grouping our unknown MOA compounds. Pearson correlation and Ward linkage calculations were used to generate a dendrogram that produced clustering largely by known MOA, although there were exceptions. Of the three unknown compounds, one was definitively placed as an anti-folate. The second and third compounds’ MOA were not clearly identified, likely due to unique MOA not represented within the commercial database. The availability of the database generated in this report for S. aureus ATCC 29213 will increase the accessibility of this technique to other investigators. From our analysis, the Phenotype Microarray system can group compounds with clear MOA, but distinction of unique or broadly acting MOA at this time is less clear. PMID:22434711

Computational, Integrative, and Comparative Methods for the Elucidation of Genetic Coexpression Networks

DOE PAGES

Baldwin, Nicole E.; Chesler, Elissa J.; Kirov, Stefan; ...

2005-01-01

Gene expression microarray data can be used for the assembly of genetic coexpression network graphs. Using mRNA samples obtained from recombinant inbred Mus musculus strains, it is possible to integrate allelic variation with molecular and higher-order phenotypes. The depth of quantitative genetic analysis of microarray data can be vastly enhanced utilizing this mouse resource in combination with powerful computational algorithms, platforms, and data repositories. The resulting network graphs transect many levels of biological scale. This approach is illustrated with the extraction of cliques of putatively co-regulated genes and their annotation using gene ontology analysis and cis -regulatory element discovery. Themore » causal basis for co-regulation is detected through the use of quantitative trait locus mapping.« less

MRI phenotypes with high neurodegeneration are associated with peripheral blood B-cell changes.

PubMed

Comabella, Manuel; Cantó, Ester; Nurtdinov, Ramil; Río, Jordi; Villar, Luisa M; Picón, Carmen; Castilló, Joaquín; Fissolo, Nicolás; Aymerich, Xavier; Auger, Cristina; Rovira, Alex; Montalban, Xavier

2016-01-15

Little is known about the mechanisms leading to neurodegeneration in multiple sclerosis (MS) and the role of peripheral blood cells in this neurodegenerative component. We aimed to correlate brain radiological phenotypes defined by high and low neurodegeneration with gene expression profiling of peripheral blood mononuclear cells (PBMC) from MS patients. Magnetic resonance imaging (MRI) scans from 64 patients with relapsing-remitting MS (RRMS) were classified into radiological phenotypes characterized by low (N = 27) and high (N = 37) neurodegeneration according to the number of contrast-enhancing lesions, the relative volume of non-enhancing black holes on T1-weighted images, and the brain parenchymal fraction. Gene expression profiling was determined in PBMC using microarrays, and validation of selected genes was performed by polymerase chain reaction (PCR). B-cell immunophenotyping was conducted by flow cytometry. Microarray analysis revealed the B-cell specific genes FCRL1, FCRL2, FCRL5 (Fc receptor-like 1, 2 and 5 respectively), and CD22 as the top differentially expressed genes between patients with high and low neurodegeneration. Levels for these genes were significantly down-regulated in PBMC from patients with MRI phenotypes characterized by high neurodegeneration and microarray findings were validated by PCR. In patients with high neurodegeneration, immunophenotyping showed a significant increase in the expression of the B-cell activation markers CD80 in naïve B cells (CD45+/CD19+/CD27-/IgD+), unswitched memory B cells (CD45+/CD19+/CD27+/IgD+), and switched memory B cells (CD45+/CD19+/CD27+/IgD-), and CD86 in naïve and switched memory B cells. These results suggest that RRMS patients with radiological phenotypes showing high neurodegeneration have changes in B cells characterized by down-regulation of B-cell-specific genes and increased activation status. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Customizing chemotherapy for colon cancer: the potential of gene expression profiling.

PubMed

Mariadason, John M; Arango, Diego; Augenlicht, Leonard H

2004-06-01

The value of gene expression profiling, or microarray analysis, for the classification and prognosis of multiple forms of cancer is now clearly established. For colon cancer, expression profiling can readily discriminate between normal and tumor tissue, and to some extent between tumors of different histopathological stage and prognosis. While a definitive in vivo study demonstrating the potential of this methodology for predicting response to chemotherapy is presently lacking, the ability of microarrays to distinguish other subtleties of colon cancer phenotype, as well as recent in vitro proof-of-principle experiments utilizing colon cancer cell lines, illustrate the potential of this methodology for predicting the probability of response to specific chemotherapeutic agents. This review discusses some of the recent advances in the use of microarray analysis for understanding and distinguishing colon cancer subtypes, and attempts to identify challenges that need to be overcome in order to achieve the goal of using gene expression profiling for customizing chemotherapy in colon cancer.

Customizing microarrays for neuroscience drug discovery.

PubMed

Girgenti, Matthew J; Newton, Samuel S

2007-08-01

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

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.

An overview of the Progenika ID CORE XT: an automated genotyping platform based on a fluidic microarray system.

PubMed

Goldman, Mindy; Núria, Núria; Castilho, Lilian M

2015-01-01

Automated testing platforms facilitate the introduction of red cell genotyping of patients and blood donors. Fluidic microarray systems, such as Luminex XMAP (Austin, TX), are used in many clinical applications, including HLA and HPA typing. The Progenika ID CORE XT (Progenika Biopharma-Grifols, Bizkaia, Spain) uses this platform to analyze 29 polymorphisms determining 37 antigens in 10 blood group systems. Once DNA has been extracted, processing time is approximately 4 hours. The system is highly automated and includes integrated analysis software that produces a file and a report with genotype and predicted phenotype results.

Identification of genes associated with the long-gut-persistence phenotype of the probiotic Lactobacillus johnsonii strain NCC533 using a combination of genomics and transcriptome analysis.

PubMed

Denou, Emmanuel; Pridmore, Raymond David; Berger, Bernard; Panoff, Jean-Michel; Arigoni, Fabrizio; Brüssow, Harald

2008-05-01

Lactobacillus johnsonii strains NCC533 and ATCC 33200 (the type strain of this species) differed significantly in gut residence time (12 versus 5 days) after oral feeding to mice. Genes affecting the long gut residence time of the probiotic strain NCC533 were targeted for analysis. We hypothesized that genes specific for this strain, which are expressed during passage of the bacterium through the gut, affect the phenotype. When the DNA of the type strain was hybridized against a microarray of the sequenced NCC533 strain, we identified 233 genes that were specific for the long-gut-persistence isolate. Whole-genome transcription analysis of the NCC533 strain using the microarray format identified 174 genes that were strongly and consistently expressed in the jejunum of mice monocolonized with this strain. Fusion of the two microarray data sets identified three gene loci that were both expressed in vivo and specific to the long-gut-persistence isolate. The identified genes included LJ1027 and LJ1028, two glycosyltransferase genes in the exopolysaccharide synthesis operon; LJ1654 to LJ1656, encoding a sugar phosphotransferase system (PTS) transporter annotated as mannose PTS; and LJ1680, whose product shares 30% amino acid identity with immunoglobulin A proteases from pathogenic bacteria. Knockout mutants were tested in vivo. The experiments revealed that deletion of LJ1654 to LJ1656 and LJ1680 decreased the gut residence time, while a mutant with a deleted exopolysaccharide biosynthesis cluster had a slightly increased residence time.

Phenotypic analysis of prostate-infiltrating lymphocytes reveals TH17 and Treg skewing.

PubMed

Sfanos, Karen Sandell; Bruno, Tullia C; Maris, Charles H; Xu, Lauren; Thoburn, Christopher J; DeMarzo, Angelo M; Meeker, Alan K; Isaacs, William B; Drake, Charles G

2008-06-01

Pathologic examination of prostate glands removed from patients with prostate cancer commonly reveals infiltrating CD4+ and CD8+ T cells. Little is known about the phenotype of these cells, despite accumulating evidence suggesting a potential role for chronic inflammation in the etiology of prostate cancer. We developed a technique that samples the majority of the peripheral prostate through serial needle aspirates. CD4+ prostate-infiltrating lymphocytes (PIL) were isolated using magnetic beads and analyzed for subset skewing using both flow cytometry and quantitative reverse transcription-PCR. The transcriptional profile of fluorescence-activated cell sorted prostate-infiltrating regulatory T cells (CD4+, CD25+, GITR+) was compared with naïve, peripheral blood T cells using microarray analysis. CD4+ PIL showed a paucity of TH2 (interleukin-4-secreting) cells, a surprising finding given the generally accepted association of these cells with chronic, smoldering inflammation. Instead, CD4+ PIL seemed to be skewed towards a regulatory Treg phenotype (FoxP3+) as well as towards the TH17 phenotype (interleukin-17+). We also found that a preponderance of TH17-mediated inflammation was associated with a lower pathologic Gleason score. These protein level data were reflected at the message level, as analyzed by quantitative reverse transcription-PCR. Microarray analysis of pooled prostate-infiltrating T(reg) revealed expected Treg-associated transcripts (FoxP3, CTLA-4, GITR, LAG-3) as well as a number of unique cell surface markers that may serve as additional Treg markers. Taken together, these data suggest that TH17 and/or Treg CD4+ T cells (rather than TH2 T cells) may be involved in the development or progression of prostate cancer.

Phenotypic Analysis of Prostate-Infiltrating Lymphocytes Reveals TH17 and Treg Skewing

PubMed Central

Sfanos, Karen Sandell; Bruno, Tullia C.; Maris, Charles H.; Xu, Lauren; Thoburn, Christopher J.; DeMarzo, Angelo M.; Meeker, Alan K.; Isaacs, William B.; Drake, Charles G.

2011-01-01

Purpose Pathologic examination of prostate glands removed from patients with prostate cancer commonly reveals infiltrating CD4+ and CD8+ T cells. Little is known about the phenotype of these cells, despite accumulating evidence suggesting a potential role for chronic inflammation in the etiology of prostate cancer. Experimental Design We developed a technique that samples the majority of the peripheral prostate through serial needle aspirates. CD4+ prostate-infiltrating lymphocytes (PIL) were isolated using magnetic beads and analyzed for subset skewing using both flow cytometry and quantitative reverse transcription-PCR. The transcriptional profile of fluorescence-activated cell sorted prostate-infiltrating regulatory T cells (CD4+, CD25+, GITR+) was compared with naïve, peripheral blood T cells using microarray analysis. Results CD4+ PIL showed a paucity of TH2 (interleukin-4– secreting) cells, a surprising finding given the generally accepted association of these cells with chronic, smoldering inflammation. Instead, CD4+ PIL seemed to be skewed towards a regulatory Treg phenotype (FoxP3+) as well as towards the TH17 phenotype (interleukin-17+). We also found that a preponderance of TH17-mediated inflammation was associated with a lower pathologic Gleason score. These protein level data were reflected at the message level, as analyzed by quantitative reverse transcription-PCR. Microarray analysis of pooled prostate-infiltrating Treg revealed expected Treg-associated transcripts (FoxP3, CTLA-4, GITR, LAG-3) as well as a number of unique cell surface markers that may serve as additional Treg markers. Conclusion Taken together, these data suggest that TH17 and/or Treg CD4+ T cells (rather than TH2 T cells) may be involved in the development or progression of prostate cancer. PMID:18519750

Correlational analysis for identifying genes whose regulation contributes to chronic neuropathic pain

PubMed Central

Persson, Anna-Karin; Gebauer, Mathias; Jordan, Suzana; Metz-Weidmann, Christiane; Schulte, Anke M; Schneider, Hans-Christoph; Ding-Pfennigdorff, Danping; Thun, Jonas; Xu, Xiao-Jun; Wiesenfeld-Hallin, Zsuzsanna; Darvasi, Ariel; Fried, Kaj; Devor, Marshall

2009-01-01

Background Nerve injury-triggered hyperexcitability in primary sensory neurons is considered a major source of chronic neuropathic pain. The hyperexcitability, in turn, is thought to be related to transcriptional switching in afferent cell somata. Analysis using expression microarrays has revealed that many genes are regulated in the dorsal root ganglion (DRG) following axotomy. But which contribute to pain phenotype versus other nerve injury-evoked processes such as nerve regeneration? Using the L5 spinal nerve ligation model of neuropathy we examined differential changes in gene expression in the L5 (and L4) DRGs in five mouse strains with contrasting susceptibility to neuropathic pain. We sought genes for which the degree of regulation correlates with strain-specific pain phenotype. Results In an initial experiment six candidate genes previously identified as important in pain physiology were selected for in situ hybridization to DRG sections. Among these, regulation of the Na+ channel α subunit Scn11a correlated with levels of spontaneous pain behavior, and regulation of the cool receptor Trpm8 correlated with heat hypersensibility. In a larger scale experiment, mRNA extracted from individual mouse DRGs was processed on Affymetrix whole-genome expression microarrays. Overall, 2552 ± 477 transcripts were significantly regulated in the axotomized L5DRG 3 days postoperatively. However, in only a small fraction of these was the degree of regulation correlated with pain behavior across strains. Very few genes in the "uninjured" L4DRG showed altered expression (24 ± 28). Conclusion Correlational analysis based on in situ hybridization provided evidence that differential regulation of Scn11a and Trpm8 contributes to across-strain variability in pain phenotype. This does not, of course, constitute evidence that the others are unrelated to pain. Correlational analysis based on microarray data yielded a larger "look-up table" of genes whose regulation likely contributes to pain variability. While this list is enriched in genes of potential importance for pain physiology, and is relatively free of the bias inherent in the candidate gene approach, additional steps are required to clarify which transcripts on the list are in fact of functional importance. PMID:19228393

Methods to study legionella transcriptome in vitro and in vivo.

PubMed

Faucher, Sebastien P; Shuman, Howard A

2013-01-01

The study of transcriptome responses can provide insight into the regulatory pathways and genetic factors that contribute to a specific phenotype. For bacterial pathogens, it can identify putative new virulence systems and shed light on the mechanisms underlying the regulation of virulence factors. Microarrays have been previously used to study gene regulation in Legionella pneumophila. In the past few years a sharp reduction of the costs associated with microarray experiments together with the availability of relatively inexpensive custom-designed commercial microarrays has made microarray technology an accessible tool for the majority of researchers. Here we describe the methodologies to conduct microarray experiments from in vitro and in vivo samples.

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

Hybrid microarray based on double biomolecular markers of DNA and carbohydrate for simultaneous genotypic and phenotypic detection of cholera toxin-producing Vibrio cholerae.

PubMed

Shin, Hwa Hui; Seo, Jeong Hyun; Kim, Chang Sup; Hwang, Byeong Hee; Cha, Hyung Joon

2016-05-15

Life-threatening diarrheal cholera is usually caused by water or food contaminated with cholera toxin-producing Vibrio cholerae. For the prevention and surveillance of cholera, it is crucial to rapidly and precisely detect and identify the etiological causes, such as V. cholerae and/or its toxin. In the present work, we propose the use of a hybrid double biomolecular marker (DBM) microarray containing 16S rRNA-based DNA capture probe to genotypically identify V. cholerae and GM1 pentasaccharide capture probe to phenotypically detect cholera toxin. We employed a simple sample preparation method to directly obtain genomic DNA and secreted cholera toxin as target materials from bacterial cells. By utilizing the constructed DBM microarray and prepared samples, V. cholerae and cholera toxin were detected successfully, selectively, and simultaneously; the DBM microarray was able to analyze the pathogenicity of the identified V. cholerae regardless of whether the bacteria produces toxin. Therefore, our proposed DBM microarray is a new effective platform for identifying bacteria and analyzing bacterial pathogenicity simultaneously. Copyright © 2015 Elsevier B.V. All rights reserved.

Potentials and capabilities of the Extracellular Vesicle (EV) Array.

PubMed

Jørgensen, Malene Møller; Bæk, Rikke; Varming, Kim

2015-01-01

Extracellular vesicles (EVs) and exosomes are difficult to enrich or purify from biofluids, hence quantification and phenotyping of these are tedious and inaccurate. The multiplexed, highly sensitive and high-throughput platform of the EV Array presented by Jørgensen et al., (J Extracell Vesicles, 2013; 2: 10) has been refined regarding the capabilities of the method for characterization and molecular profiling of EV surface markers. Here, we present an extended microarray platform to detect and phenotype plasma-derived EVs (optimized for exosomes) for up to 60 antigens without any enrichment or purification prior to analysis.

Quantitative phenotyping via deep barcode sequencing.

PubMed

Smith, Andrew M; Heisler, Lawrence E; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J; Chee, Mark; Roth, Frederick P; Giaever, Guri; Nislow, Corey

2009-10-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or "Bar-seq," outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that approximately 20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene-environment interactions on a genome-wide scale.

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

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

Elucidation of the Metabolic Network of Helicobacter pylori J99 and Malaysian Clinical Strains by Phenotype Microarray.

PubMed

Lee, Woon Ching; Goh, Khean Lee; Loke, Mun Fai; Vadivelu, Jamuna

2017-02-01

Helicobacter pylori colonizes almost half of the human population worldwide. H. pylori strains are genetically diverse, and the specific genotypes are associated with various clinical manifestations including gastric adenocarcinoma, peptic ulcer disease (PUD), and nonulcer dyspepsia (NUD). However, our current knowledge of the H. pylori metabolism is limited. To understand the metabolic differences among H. pylori strains, we investigated four Malaysian H. pylori clinical strains, which had been previously sequenced, and a standard strain, H. pylori J99, at the phenotypic level. The phenotypes of the H. pylori strains were profiled using the Biolog Phenotype Microarray system to corroborate genomic data. We initiated the analyses by predicting carbon and nitrogen metabolic pathways from the H. pylori genomic data from the KEGG database. Biolog PM aided the validation of the prediction and provided a more intensive analysis of the H. pylori phenomes. We have identified a core set of metabolic nutrient sources that was utilized by all strains tested and another set that was differentially utilized by only the local strains. Pentose sugars are the preferred carbon nutrients utilized by H. pylori. The amino acids l-aspartic acid, d-alanine, and l-asparagine serve as both carbon and nitrogen sources in the metabolism of the bacterium. The phenotypic profile based on this study provides a better understanding on the survival of H. pylori in its natural host. Our data serve as a foundation for future challenges in correlating interstrain metabolic differences in H. pylori. © 2016 The Authors. Helicobacter Published by John Wiley & Sons Ltd.

Phenotypic Analysis of Korean Patients with Abnormal Chromosomal Microarray in Patients with Unexplained Developmental Delay/Intellectual Disability.

PubMed

Kim, Hyo Jeong; Park, Chang Il; Lim, Jae Woo; Lee, Gyung Min; Cho, Eunhae; Kim, Hyon J

2018-05-01

The present study aimed to investigate chromosomal microarray (CMA) and clinical data in patients with unexplained developmental delay/intellectual disability (DD/ID) accompanying dysmorphism, congenital anomalies, or epilepsy. We also aimed to evaluate phenotypic clues in patients with pathogenic copy number variants (CNVs). We collected clinical and CMA data from patients at Konyang University Hospital between September 2013 and October 2014. We included patients who had taken the CMA test to evaluate the etiology of unexplained DD/ID. All of the 50 patients identified had DD/ID. Thirty-nine patients had dysmorphism, 19 patients suffered from epilepsy, and 12 patients had congenital anomalies. Twenty-nine of the 50 patients (58%) showed abnormal results. Eighteen (36%) were considered to have pathogenic CNVs. Dysmorphism (p=0.028) was significantly higher in patients with pathogenic CNVs than in those with normal CMA. Two or more clinical features were presented by 61.9% (13/21) of the patients with normal CMA and by 83.3% (15/18) of the patients with pathogenic CMA. Dysmorphism can be a phenotypic clue to pathogenic CNVs. Furthermore, pathogenic CNV might be more frequently found if patients have two or more clinical features in addition to DD/ID. © Copyright: Yonsei University College of Medicine 2018.

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Characterization of a complex chromosomal rearrangement using chromosome, FISH, and microarray assays in a girl with multiple congenital abnormalities and developmental delay.

PubMed

Hemmat, Morteza; Yang, Xiaojing; Chan, Patricia; McGough, Robert A; Ross, Leslie; Mahon, Loretta W; Anguiano, Arturo L; Boris, Wang T; Elnaggar, Mohamed M; Wang, Jia-Chi J; Strom, Charles M; Boyar, Fatih Z

2014-01-01

Complex chromosomal rearrangements (CCRs) are balanced or unbalanced structural rearrangements involving three or more cytogenetic breakpoints on two or more chromosomal pairs. The phenotypic anomalies in such cases are attributed to gene disruption, superimposed cryptic imbalances in the genome, and/or position effects. We report a 14-year-old girl who presented with multiple congenital anomalies and developmental delay. Chromosome and FISH analysis indicated a highly complex chromosomal rearrangement involving three chromosomes (3, 7 and 12), seven breakpoints as a result of one inversion, two insertions, and two translocations forming three derivative chromosomes. Additionally, chromosomal microarray study (CMA) revealed two submicroscopic deletions at 3p12.3 (467 kb) and 12q13.12 (442 kb). We postulate that microdeletion within the ROBO1 gene at 3p12.3 may have played a role in the patient's developmental delay, since it has potential activity-dependent role in neurons. Additionally, factors other than genomic deletions such as loss of function or position effects may also contribute to the abnormal phenotype in our patient.

Identification of the TFII-I family target genes in the vertebrate genome.

PubMed

Chimge, Nyam-Osor; Makeyev, Aleksandr V; Ruddle, Frank H; Bayarsaihan, Dashzeveg

2008-07-01

GTF2I and GTF2IRD1 encode members of the TFII-I transcription factor family and are prime candidates in the Williams syndrome, a complex neurodevelopmental disorder. Our previous expression microarray studies implicated TFII-I proteins in the regulation of a number of genes critical in various aspects of cell physiology. Here, we combined bioinformatics and microarray results to identify TFII-I downstream targets in the vertebrate genome. These results were validated by chromatin immunoprecipitation and siRNA analysis. The collected evidence revealed the complexity of TFII-I-mediated processes that involve distinct regulatory networks. Altogether, these results lead to a better understanding of specific molecular events, some of which may be responsible for the Williams syndrome phenotype.

Microarray RNA expression analysis of cerebral white matter lesions reveals changes in multiple functional pathways.

PubMed

Simpson, Julie E; Hosny, Ola; Wharton, Stephen B; Heath, Paul R; Holden, Hazel; Fernando, Malee S; Matthews, Fiona; Forster, Gill; O'Brien, John T; Barber, Robert; Kalaria, Raj N; Brayne, Carol; Shaw, Pamela J; Lewis, Claire E; Ince, Paul G

2009-02-01

White matter lesions (WML) in brain aging are linked to dementia and depression. Ischemia contributes to their pathogenesis but other mechanisms may contribute. We used RNA microarray analysis with functional pathway grouping as an unbiased approach to investigate evidence for additional pathogenetic mechanisms. WML were identified by MRI and pathology in brains donated to the Medical Research Council Cognitive Function and Ageing Study Cognitive Function and Aging Study. RNA was extracted to compare WML with nonlesional white matter samples from cases with lesions (WM[L]), and from cases with no lesions (WM[C]) using RNA microarray and pathway analysis. Functional pathways were validated for selected genes by quantitative real-time polymerase chain reaction and immunocytochemistry. We identified 8 major pathways in which multiple genes showed altered RNA transcription (immune regulation, cell cycle, apoptosis, proteolysis, ion transport, cell structure, electron transport, metabolism) among 502 genes that were differentially expressed in WML compared to WM[C]. In WM[L], 409 genes were altered involving the same pathways. Genes selected to validate this microarray data all showed the expected changes in RNA levels and immunohistochemical expression of protein. WML represent areas with a complex molecular phenotype. From this and previous evidence, WML may arise through tissue ischemia but may also reflect the contribution of additional factors like blood-brain barrier dysfunction. Differential expression of genes in WM[L] compared to WM[C] indicate a "field effect" in the seemingly normal surrounding white matter.

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.

Identification of a transcriptional signature for the wound healing continuum

PubMed Central

Peake, Matthew A; Caley, Mathew; Giles, Peter J; Wall, Ivan; Enoch, Stuart; Davies, Lindsay C; Kipling, David; Thomas, David W; Stephens, Phil

2014-01-01

There is a spectrum/continuum of adult human wound healing outcomes ranging from the enhanced (nearly scarless) healing observed in oral mucosa to scarring within skin and the nonhealing of chronic skin wounds. Central to these outcomes is the role of the fibroblast. Global gene expression profiling utilizing microarrays is starting to give insight into the role of such cells during the healing process, but no studies to date have produced a gene signature for this wound healing continuum. Microarray analysis of adult oral mucosal fibroblast (OMF), normal skin fibroblast (NF), and chronic wound fibroblast (CWF) at 0 and 6 hours post-serum stimulation was performed. Genes whose expression increases following serum exposure in the order OMF < NF < CWF are candidates for a negative/impaired healing phenotype (the dysfunctional healing group), whereas genes with the converse pattern are potentially associated with a positive/preferential healing phenotype (the enhanced healing group). Sixty-six genes in the enhanced healing group and 38 genes in the dysfunctional healing group were identified. Overrepresentation analysis revealed pathways directly and indirectly associated with wound healing and aging and additional categories associated with differentiation, development, and morphogenesis. Knowledge of this wound healing continuum gene signature may in turn assist in the therapeutic assessment/treatment of a patient's wounds. PMID:24844339

Systematic validation and atomic force microscopy of non-covalent short oligonucleotide barcode microarrays.

PubMed

Cook, Michael A; Chan, Chi-Kin; Jorgensen, Paul; Ketela, Troy; So, Daniel; Tyers, Mike; Ho, Chi-Yip

2008-02-06

Molecular barcode arrays provide a powerful means to analyze cellular phenotypes in parallel through detection of short (20-60 base) unique sequence tags, or "barcodes", associated with each strain or clone in a collection. However, costs of current methods for microarray construction, whether by in situ oligonucleotide synthesis or ex situ coupling of modified oligonucleotides to the slide surface are often prohibitive to large-scale analyses. Here we demonstrate that unmodified 20mer oligonucleotide probes printed on conventional surfaces show comparable hybridization signals to covalently linked 5'-amino-modified probes. As a test case, we undertook systematic cell size analysis of the budding yeast Saccharomyces cerevisiae genome-wide deletion collection by size separation of the deletion pool followed by determination of strain abundance in size fractions by barcode arrays. We demonstrate that the properties of a 13K unique feature spotted 20 mer oligonucleotide barcode microarray compare favorably with an analogous covalently-linked oligonucleotide array. Further, cell size profiles obtained with the size selection/barcode array approach recapitulate previous cell size measurements of individual deletion strains. Finally, through atomic force microscopy (AFM), we characterize the mechanism of hybridization to unmodified barcode probes on the slide surface. These studies push the lower limit of probe size in genome-scale unmodified oligonucleotide microarray construction and demonstrate a versatile, cost-effective and reliable method for molecular barcode analysis.

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.

Roles of the Sodium-Translocating NADH:Quinone Oxidoreductase (Na+-NQR) on Vibrio cholerae Metabolism, Motility and Osmotic Stress Resistance

PubMed Central

Minato, Yusuke; Halang, Petra; Quinn, Matthew J.; Faulkner, Wyatt J.; Aagesen, Alisha M.; Steuber, Julia; Stevens, Jan F.; Häse, Claudia C.

2014-01-01

The Na+ translocating NADH:quinone oxidoreductase (Na+-NQR) is a unique respiratory enzyme catalyzing the electron transfer from NADH to quinone coupled with the translocation of sodium ions across the membrane. Typically, Vibrio spp., including Vibrio cholerae, have this enzyme but lack the proton-pumping NADH:ubiquinone oxidoreductase (Complex I). Thus, Na+-NQR should significantly contribute to multiple aspects of V. cholerae physiology; however, no detailed characterization of this aspect has been reported so far. In this study, we broadly investigated the effects of loss of Na+-NQR on V. cholerae physiology by using Phenotype Microarray (Biolog), transcriptome and metabolomics analyses. We found that the V. cholerae ΔnqrA-F mutant showed multiple defects in metabolism detected by Phenotype Microarray. Transcriptome analysis revealed that the V. cholerae ΔnqrA-F mutant up-regulates 31 genes and down-regulates 55 genes in both early and mid-growth phases. The most up-regulated genes included the cadA and cadB genes, encoding a lysine decarboxylase and a lysine/cadaverine antiporter, respectively. Increased CadAB activity was further suggested by the metabolomics analysis. The down-regulated genes include sialic acid catabolism genes. Metabolomic analysis also suggested increased reductive pathway of TCA cycle and decreased purine metabolism in the V. cholerae ΔnqrA-F mutant. Lack of Na+-NQR did not affect any of the Na+ pumping-related phenotypes of V. cholerae suggesting that other secondary Na+ pump(s) can compensate for Na+ pumping activity of Na+-NQR. Overall, our study provides important insights into the contribution of Na+-NQR to V. cholerae physiology. PMID:24811312

Quantitative phenotyping via deep barcode sequencing

PubMed Central

Smith, Andrew M.; Heisler, Lawrence E.; Mellor, Joseph; Kaper, Fiona; Thompson, Michael J.; Chee, Mark; Roth, Frederick P.; Giaever, Guri; Nislow, Corey

2009-01-01

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or “Bar-seq,” outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that ∼20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene–environment interactions on a genome-wide scale. PMID:19622793

[Phenotype-genotype correlation analysis of 12 cases with Angelman/Prader-Willi syndrome].

PubMed

Chen, Chen; Peng, Ying; Xia, Yan; Li, Haoxian; Zhu, Huimin; Pan, Qian; Yin, Fei; Wu, Lingqian

2014-12-01

To investigate the genotype-phenotype correlation in patients with Angelman syndrome/Prader-Willi syndrome (AS/PWS) and assess the application value of high-resolution single nucleotide polymorphism microarrays (SNP array) for such diseases. Twelve AS/PWS patients were diagnosed through SNP array, fluorescence in situ hybridization (FISH) and karyotype analysis. Clinical characteristics were analyzed. Deletions ranging from 4.8 Mb to 7.0 Mb on chromosome 15q11.2-13 were detected in 11 patients. Uniparental disomy (UPD) was detected in only 1 patient. Patients with deletions could be divided into 2 groups, including 7 cases with class I and 4 with class II. The two groups however had no significant phenotypic difference. The UPD patient had relatively better development and language ability. Deletions of 6 patients were confirmed by FISH to be of de novo in origin. The risk to their sibs was determined to be less than 1%. The phenotypic differences between AS/PWS patients with class I and class II deletion need to be further studied. SNP array is useful in detecting and distinguishing of patients with deletion or UPD. This method may be applied for studying the genotype-phenotype association and the mechanism underlying AS/PWS.

Surprisal analysis of Glioblastoma Multiform (GBM) microRNA dynamics unveils tumor specific phenotype.

PubMed

Zadran, Sohila; Remacle, Francoise; Levine, Raphael

2014-01-01

Gliomablastoma multiform (GBM) is the most fatal form of all brain cancers in humans. Currently there are limited diagnostic tools for GBM detection. Here, we applied surprisal analysis, a theory grounded in thermodynamics, to unveil how biomolecule energetics, specifically a redistribution of free energy amongst microRNAs (miRNAs), results in a system deviating from a non-cancer state to the GBM cancer -specific phenotypic state. Utilizing global miRNA microarray expression data of normal and GBM patients tumors, surprisal analysis characterizes a miRNA system response capable of distinguishing GBM samples from normal tissue biopsy samples. We indicate that the miRNAs contributing to this system behavior is a disease phenotypic state specific to GBM and is therefore a unique GBM-specific thermodynamic signature. MiRNAs implicated in the regulation of stochastic signaling processes crucial in the hallmarks of human cancer, dominate this GBM-cancer phenotypic state. With this theory, we were able to distinguish with high fidelity GBM patients solely by monitoring the dynamics of miRNAs present in patients' biopsy samples. We anticipate that the GBM-specific thermodynamic signature will provide a critical translational tool in better characterizing cancer types and in the development of future therapeutics for GBM.

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

NASA Technical Reports Server (NTRS)

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 x g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies.

Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

PubMed

Tian, Ye; Wang, Sean S; Zhang, Zhen; Rodriguez, Olga C; Petricoin, Emanuel; Shih, Ie-Ming; Chan, Daniel; Avantaggiati, Maria; Yu, Guoqiang; Ye, Shaozhen; Clarke, Robert; Wang, Chao; Zhang, Bai; Wang, Yue; Albanese, Chris

2014-01-01

Ever growing "omics" data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning. Analysis of Space Grown Arabidopsis with Microarray Data from GeneLab: Identification of Genes Important in Vascular Patterning

NASA Technical Reports Server (NTRS)

Weitzel, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

2016-01-01

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Phenotypic and genomic responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis germinants

EPA Science Inventory

The effects of exposure to two nanoparticles (NPs) -titanium dioxide (nano-titania) and cerium oxide (nano-ceria) at 500 mg NPs L-1 on gene expression and growth in Arabidopsis thaliana germinants were studied using microarrays and phenotype studies. After 12 days post treatment,...

Calorie restriction ameliorates neurodegenerative phenotypes in forebrain-specific presenilin-1 and presenilin-2 double knockout mice.

PubMed

Wu, Pu; Shen, Qian; Dong, Suzhen; Xu, Zhiliang; Tsien, Joe Z; Hu, Yinghe

2008-10-01

Conditional double knockout of presenilin-1 and presenilin-2 (cDKO) in forebrain of mice led to brain atrophy, tau hyperphosphorylation, synaptic dysfunction and cognitive deficit. These brain changes recapitulated most of the neurodegenerative phenotypes of Alzheimer's disease (AD). In this report, we have investigated the effects of 4-month calorie restriction (CR) regimen on different phenotypes in cDKO mice. We found that CR improved novel object recognition and contextual fear conditioning memory in the cDKO mice. Histological and biochemical analysis showed that CR attenuated ventricle enlargement, caspase-3 activation and astrogliosis. In addition, the induction of tau hyperphosphorylation in the cDKO mice was reduced by CR, possibly through reduction of p25 accumulation and aberrant CDK5 activation. Finally, DNA microarray analysis demonstrated that CR could increase the expression of neurogenesis related genes and decrease the expression of inflammation related genes in the hippocampus of cDKO mice. The possible molecular mechanisms of the CR effects on alleviating AD pathogenesis have been discussed.

Extracellular Vesicle (EV) Array: microarray capturing of exosomes and other extracellular vesicles for multiplexed phenotyping.

PubMed

Jørgensen, Malene; Bæk, Rikke; Pedersen, Shona; Søndergaard, Evo K L; Kristensen, Søren R; Varming, Kim

2013-01-01

Exosomes are one of the several types of cell-derived vesicles with a diameter of 30-100 nm. These extracellular vesicles are recognized as potential markers of human diseases such as cancer. However, their use in diagnostic tests requires an objective and high-throughput method to define their phenotype and determine their concentration in biological fluids. To identify circulating as well as cell culture-derived vesicles, the current standard is immunoblotting or a flow cytometrical analysis for specific proteins, both of which requires large amounts of purified vesicles. Based on the technology of protein microarray, we hereby present a highly sensitive Extracellular Vesicle (EV) Array capable of detecting and phenotyping exosomes and other extracellular vesicles from unpurified starting material in a high-throughput manner. To only detect the exosomes captured on the EV Array, a cocktail of antibodies against the tetraspanins CD9, CD63 and CD81 was used. These antibodies were selected to ensure that all exosomes captured are detected, and concomitantly excluding the detection of other types of microvesicles. The limit of detection (LOD) was determined on exosomes derived from the colon cancer cell line LS180. It clarified that supernatant from only approximately 10(4) cells was needed to obtain signals or that only 2.5×10(4) exosomes were required for each microarray spot (~1 nL). Phenotyping was performed on plasma (1-10 µL) from 7 healthy donors, which were applied to the EV Array with a panel of antibodies against 21 different cellular surface antigens and cancer antigens. For each donor, there was considerable heterogeneity in the expression levels of individual markers. The protein profiles of the exosomes (defined as positive for CD9, CD63 and CD81) revealed that only the expression level of CD9 and CD81 was approximately equal in the 7 donors. This implies questioning the use of CD63 as a standard exosomal marker since the expression level of this tetraspanin was considerably lower.

Restriction Site Tiling Analysis: accurate discovery and quantitative genotyping of genome-wide polymorphisms using nucleotide arrays

PubMed Central

2010-01-01

High-throughput genotype data can be used to identify genes important for local adaptation in wild populations, phenotypes in lab stocks, or disease-related traits in human medicine. Here we advance microarray-based genotyping for population genomics with Restriction Site Tiling Analysis. The approach simultaneously discovers polymorphisms and provides quantitative genotype data at 10,000s of loci. It is highly accurate and free from ascertainment bias. We apply the approach to uncover genomic differentiation in the purple sea urchin. PMID:20403197

Genome‐Wide MicroRNA and Gene Analysis of Mesenchymal Stem Cell Chondrogenesis Identifies an Essential Role and Multiple Targets for miR‐140‐5p

PubMed Central

Tselepi, Maria; Gómez, Rodolfo; Woods, Steven; Hui, Wang; Smith, Graham R.; Shanley, Daryl P.; Clark, Ian M.; Young, David A.

2015-01-01

Abstract microRNAs (miRNAs) are abundantly expressed in development where they are critical determinants of cell differentiation and phenotype. Accordingly miRNAs are essential for normal skeletal development and chondrogenesis in particular. However, the question of which miRNAs are specific to the chondrocyte phenotype has not been fully addressed. Using microarray analysis of miRNA expression during mesenchymal stem cell chondrogenic differentiation and detailed examination of the role of essential differentiation factors, such as SOX9, TGF‐β, and the cell condensation phase, we characterize the repertoire of specific miRNAs involved in chondrocyte development, highlighting in particular miR‐140 and miR‐455. Further with the use of mRNA microarray data we integrate miRNA expression and mRNA expression during chondrogenesis to underline the particular importance of miR‐140, especially the ‐5p strand. We provide a detailed identification and validation of direct targets of miR‐140‐5p in both chondrogenesis and adult chondrocytes with the use of microarray and 3′UTR analysis. This emphasizes the diverse array of targets and pathways regulated by miR‐140‐5p. We are also able to confirm previous experimentally identified targets but, additionally, identify a novel positive regulation of the Wnt signaling pathway by miR‐140‐5p. Wnt signaling has a complex role in chondrogenesis and skeletal development and these findings illustrate a previously unidentified role for miR‐140‐5p in regulation of Wnt signaling in these processes. Together these developments further highlight the role of miRNAs during chondrogenesis to improve our understanding of chondrocyte development and guide cartilage tissue engineering. Stem Cells 2015;33:3266–3280 PMID:26175215

Comparison of Chemical Sensitivity of Fresh and Long-Stored Heat Resistant Neosartorya fischeri Environmental Isolates Using BIOLOG Phenotype MicroArray System

PubMed Central

Panek, Jacek; Frąc, Magdalena; Bilińska-Wielgus, Nina

2016-01-01

Spoilage of heat processed food and beverage by heat resistant fungi (HRF) is a major problem for food industry in many countries. Neosartorya fischeri is the leading source of spoilage in thermally processed products. Its resistance to heat processing and toxigenicity makes studies about Neosartorya fischeri metabolism and chemical sensitivity essential. In this study chemical sensitivity of two environmental Neosartorya fischeri isolates were compared. One was isolated from canned apples in 1923 (DSM3700), the other from thermal processed strawberry product in 2012 (KC179765), used as long-stored and fresh isolate, respectively. The study was conducted using Biolog Phenotype MicroArray platforms of chemical sensitivity panel and traditional hole-plate method. The study allowed for obtaining data about Neosartorya fischeri growth inhibitors. The fresh isolate appeared to be much more resistant to chemical agents than the long-stored isolate. Based on phenotype microarray assay nitrogen compounds, toxic cations and membrane function compounds were the most effective in growth inhibition of N. fischeri isolates. According to the study zaragozic acid A, thallium(I) acetate and sodium selenate were potent and promising N. fischeri oriented fungicides which was confirmed by both chemical sensitivity microplates panel and traditional hole-plate methods. PMID:26815302

Characterization of a complex chromosomal rearrangement using chromosome, FISH, and microarray assays in a girl with multiple congenital abnormalities and developmental delay

PubMed Central

2014-01-01

Complex chromosomal rearrangements (CCRs) are balanced or unbalanced structural rearrangements involving three or more cytogenetic breakpoints on two or more chromosomal pairs. The phenotypic anomalies in such cases are attributed to gene disruption, superimposed cryptic imbalances in the genome, and/or position effects. We report a 14-year-old girl who presented with multiple congenital anomalies and developmental delay. Chromosome and FISH analysis indicated a highly complex chromosomal rearrangement involving three chromosomes (3, 7 and 12), seven breakpoints as a result of one inversion, two insertions, and two translocations forming three derivative chromosomes. Additionally, chromosomal microarray study (CMA) revealed two submicroscopic deletions at 3p12.3 (467 kb) and 12q13.12 (442 kb). We postulate that microdeletion within the ROBO1 gene at 3p12.3 may have played a role in the patient’s developmental delay, since it has potential activity-dependent role in neurons. Additionally, factors other than genomic deletions such as loss of function or position effects may also contribute to the abnormal phenotype in our patient. PMID:25478007

Simultaneous clustering of gene expression data with clinical chemistry and pathological evaluations reveals phenotypic prototypes

PubMed Central

Bushel, Pierre R; Wolfinger, Russell D; Gibson, Greg

2007-01-01

Background Commonly employed clustering methods for analysis of gene expression data do not directly incorporate phenotypic data about the samples. Furthermore, clustering of samples with known phenotypes is typically performed in an informal fashion. The inability of clustering algorithms to incorporate biological data in the grouping process can limit proper interpretation of the data and its underlying biology. Results We present a more formal approach, the modk-prototypes algorithm, for clustering biological samples based on simultaneously considering microarray gene expression data and classes of known phenotypic variables such as clinical chemistry evaluations and histopathologic observations. The strategy involves constructing an objective function with the sum of the squared Euclidean distances for numeric microarray and clinical chemistry data and simple matching for histopathology categorical values in order to measure dissimilarity of the samples. Separate weighting terms are used for microarray, clinical chemistry and histopathology measurements to control the influence of each data domain on the clustering of the samples. The dynamic validity index for numeric data was modified with a category utility measure for determining the number of clusters in the data sets. A cluster's prototype, formed from the mean of the values for numeric features and the mode of the categorical values of all the samples in the group, is representative of the phenotype of the cluster members. The approach is shown to work well with a simulated mixed data set and two real data examples containing numeric and categorical data types. One from a heart disease study and another from acetaminophen (an analgesic) exposure in rat liver that causes centrilobular necrosis. Conclusion The modk-prototypes algorithm partitioned the simulated data into clusters with samples in their respective class group and the heart disease samples into two groups (sick and buff denoting samples having pain type representative of angina and non-angina respectively) with an accuracy of 79%. This is on par with, or better than, the assignment accuracy of the heart disease samples by several well-known and successful clustering algorithms. Following modk-prototypes clustering of the acetaminophen-exposed samples, informative genes from the cluster prototypes were identified that are descriptive of, and phenotypically anchored to, levels of necrosis of the centrilobular region of the rat liver. The biological processes cell growth and/or maintenance, amine metabolism, and stress response were shown to discern between no and moderate levels of acetaminophen-induced centrilobular necrosis. The use of well-known and traditional measurements directly in the clustering provides some guarantee that the resulting clusters will be meaningfully interpretable. PMID:17408499

Systematic Validation and Atomic Force Microscopy of Non-Covalent Short Oligonucleotide Barcode Microarrays

PubMed Central

Cook, Michael A.; Chan, Chi-Kin; Jorgensen, Paul; Ketela, Troy; So, Daniel; Tyers, Mike; Ho, Chi-Yip

2008-01-01

Background Molecular barcode arrays provide a powerful means to analyze cellular phenotypes in parallel through detection of short (20–60 base) unique sequence tags, or “barcodes”, associated with each strain or clone in a collection. However, costs of current methods for microarray construction, whether by in situ oligonucleotide synthesis or ex situ coupling of modified oligonucleotides to the slide surface are often prohibitive to large-scale analyses. Methodology/Principal Findings Here we demonstrate that unmodified 20mer oligonucleotide probes printed on conventional surfaces show comparable hybridization signals to covalently linked 5′-amino-modified probes. As a test case, we undertook systematic cell size analysis of the budding yeast Saccharomyces cerevisiae genome-wide deletion collection by size separation of the deletion pool followed by determination of strain abundance in size fractions by barcode arrays. We demonstrate that the properties of a 13K unique feature spotted 20 mer oligonucleotide barcode microarray compare favorably with an analogous covalently-linked oligonucleotide array. Further, cell size profiles obtained with the size selection/barcode array approach recapitulate previous cell size measurements of individual deletion strains. Finally, through atomic force microscopy (AFM), we characterize the mechanism of hybridization to unmodified barcode probes on the slide surface. Conclusions/Significance These studies push the lower limit of probe size in genome-scale unmodified oligonucleotide microarray construction and demonstrate a versatile, cost-effective and reliable method for molecular barcode analysis. PMID:18253494

Genotyping microarray (gene chip) for the ABCR (ABCA4) gene.

PubMed

Jaakson, K; Zernant, J; Külm, M; Hutchinson, A; Tonisson, N; Glavac, D; Ravnik-Glavac, M; Hawlina, M; Meltzer, M R; Caruso, R C; Testa, F; Maugeri, A; Hoyng, C B; Gouras, P; Simonelli, F; Lewis, R A; Lupski, J R; Cremers, F P M; Allikmets, R

2003-11-01

Genetic variation in the ABCR (ABCA4) gene has been associated with five distinct retinal phenotypes, including Stargardt disease/fundus flavimaculatus (STGD/FFM), cone-rod dystrophy (CRD), and age-related macular degeneration (AMD). Comparative genetic analyses of ABCR variation and diagnostics have been complicated by substantial allelic heterogeneity and by differences in screening methods. To overcome these limitations, we designed a genotyping microarray (gene chip) for ABCR that includes all approximately 400 disease-associated and other variants currently described, enabling simultaneous detection of all known ABCR variants. The ABCR genotyping microarray (the ABCR400 chip) was constructed by the arrayed primer extension (APEX) technology. Each sequence change in ABCR was included on the chip by synthesis and application of sequence-specific oligonucleotides. We validated the chip by screening 136 confirmed STGD patients and 96 healthy controls, each of whom we had analyzed previously by single strand conformation polymorphism (SSCP) technology and/or heteroduplex analysis. The microarray was >98% effective in determining the existing genetic variation and was comparable to direct sequencing in that it yielded many sequence changes undetected by SSCP. In STGD patient cohorts, the efficiency of the array to detect disease-associated alleles was between 54% and 78%, depending on the ethnic composition and degree of clinical and molecular characterization of a cohort. In addition, chip analysis suggested a high carrier frequency (up to 1:10) of ABCR variants in the general population. The ABCR genotyping microarray is a robust, cost-effective, and comprehensive screening tool for variation in one gene in which mutations are responsible for a substantial fraction of retinal disease. The ABCR chip is a prototype for the next generation of screening and diagnostic tools in ophthalmic genetics, bridging clinical and scientific research. Copyright 2003 Wiley-Liss, Inc.

Rare genomic rearrangement in a boy with Williams-Beuren syndrome associated to XYY syndrome and intriguing behavior.

PubMed

Dutra, Roberta L; Piazzon, Flavia B; Zanardo, Évelin A; Costa, Thais Virginia Moura Machado; Montenegro, Marília M; Novo-Filho, Gil M; Dias, Alexandre T; Nascimento, Amom M; Kim, Chong Ae; Kulikowski, Leslie D

2015-12-01

Williams-Beuren syndrome (WBS) is caused by a hemizygous contiguous gene microdeletion of 1.55-1.84 Mb at 7q11.23 region. Approximately, 28 genes have been shown to contribute to classical phenotype of SWB with presence of dysmorphic facial features, supravalvular aortic stenosis (SVAS), intellectual disability, and overfriendliness. With the use of Microarray-based comparative genomic hybridization and other molecular cytogenetic techniques, is possible define with more accuracy partial or atypical deletion and refine the genotype-phenotype correlation. Here, we report on a rare genomic structural rearrangement in a boy with atypical deletion in 7q11.23 and XYY syndrome with characteristic clinical signs, but not sufficient for the diagnosis of WBS. Cytogenetic analysis of G-banding showed a karyotype 47,XYY. Analysis of DNA with the technique of MLPA (Multiplex Ligation-dependent Probe Amplification) using kits a combination of kits (P064, P036, P070, and P029) identified an atypical deletion on 7q11.23. In addition, high resolution SNP Oligonucleotide Microarray Analysis (SNP-array) confirmed the alterations found by MLPA and revealed others pathogenic CNVs, in the chromosomes 7 and X. The present report demonstrates an association not yet described in literature, between Williams-Beuren syndrome and 47,XYY. The identification of atypical deletion in 7q11.23 concomitant to additional pathogenic CNVs in others genomic regions allows a better comprehension of clinical consequences of atypical genomic rearrangements. © 2015 Wiley Periodicals, Inc.

EZH2 is a mediator of EWS/FLI1 driven tumor growth and metastasis blocking endothelial and neuro-ectodermal differentiation

PubMed Central

Richter, Günther H. S.; Plehm, Stephanie; Fasan, Annette; Rössler, Sabine; Unland, Rebekka; Bennani-Baiti, Idriss M.; Hotfilder, Marc; Löwel, Diana; von Luettichau, Irene; Mossbrugger, Ilona; Quintanilla-Martinez, Leticia; Kovar, Heinrich; Staege, Martin S.; Müller-Tidow, Carsten; Burdach, Stefan

2009-01-01

Ewing tumors (ET) are highly malignant, localized in bone or soft tissue, and are molecularly defined by ews/ets translocations. DNA microarray analysis revealed a relationship of ET to both endothelium and fetal neural crest. We identified expression of histone methyltransferase enhancer of Zeste, Drosophila, Homolog 2 (EZH2) to be increased in ET. Suppressive activity of EZH2 maintains stemness in normal and malignant cells. Here, we found EWS/FLI1 bound to the EZH2 promoter in vivo, and induced EZH2 expression in ET and mesenchymal stem cells. Down-regulation of EZH2 by RNA interference in ET suppressed oncogenic transformation by inhibiting clonogenicity in vitro. Similarly, tumor development and metastasis was suppressed in immunodeficient Rag2−/−γC−/− mice. EZH2-mediated gene silencing was shown to be dependent on histone deacetylase (HDAC) activity. Subsequent microarray analysis of EZH2 knock down, HDAC-inhibitor treatment and confirmation in independent assays revealed an undifferentiated phenotype maintained by EZH2 in ET. EZH2 regulated stemness genes such as nerve growth factor receptor (NGFR), as well as genes involved in neuroectodermal and endothelial differentiation (EMP1, EPHB2, GFAP, and GAP43). These data suggest that EZH2 might have a central role in ET pathology by shaping the oncogenicity and stem cell phenotype of this tumor. PMID:19289832

Prenatal metformin exposure in mice programs the metabolic phenotype of the offspring during a high fat diet at adulthood.

PubMed

Salomäki, Henriikka; Vähätalo, Laura H; Laurila, Kirsti; Jäppinen, Norma T; Penttinen, Anna-Maija; Ailanen, Liisa; Ilyasizadeh, Juan; Pesonen, Ullamari; Koulu, Markku

2013-01-01

The antidiabetic drug metformin is currently used prior and during pregnancy for polycystic ovary syndrome, as well as during gestational diabetes mellitus. We investigated the effects of prenatal metformin exposure on the metabolic phenotype of the offspring during adulthood in mice. Metformin (300 mg/kg) or vehicle was administered orally to dams on regular diet from the embryonic day E0.5 to E17.5. Gene expression profiles in liver and brain were analysed from 4-day old offspring by microarray. Body weight development and several metabolic parameters of offspring were monitored both during regular diet (RD-phase) and high fat diet (HFD-phase). At the end of the study, two doses of metformin or vehicle were given acutely to mice at the age of 20 weeks, and Insig-1 and GLUT4 mRNA expressions in liver and fat tissue were analysed using qRT-PCR. Metformin exposed fetuses were lighter at E18.5. There was no effect of metformin on the maternal body weight development or food intake. Metformin exposed offspring gained more body weight and mesenteric fat during the HFD-phase. The male offspring also had impaired glucose tolerance and elevated fasting glucose during the HFD-phase. Moreover, the expression of GLUT4 mRNA was down-regulated in epididymal fat in male offspring prenatally exposed to metformin. Based on the microarray and subsequent qRT-PCR analyses, the expression of Insig-1 was changed in the liver of neonatal mice exposed to metformin prenatally. Furthermore, metformin up-regulated the expression of Insig-1 later in development. Gene set enrichment analysis based on preliminary microarray data identified several differentially enriched pathways both in control and metformin exposed mice. The present study shows that prenatal metformin exposure causes long-term programming effects on the metabolic phenotype during high fat diet in mice. This should be taken into consideration when using metformin as a therapeutic agent during pregnancy.

Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics.

PubMed

Vaas, Lea A I; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data.

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

PubMed Central

Vaas, Lea A. I.; Sikorski, Johannes; Michael, Victoria; Göker, Markus; Klenk, Hans-Peter

2012-01-01

Background The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed ‘-omics’ techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves. Methodology The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats. Conclusions We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data. PMID:22536335

Two stable variants of Burkholderia pseudomallei strain MSHR5848 express broadly divergent in vitro phenotypes associated with their virulence differences.

PubMed

Shea, A A; Bernhards, R C; Cote, C K; Chase, C J; Koehler, J W; Klimko, C P; Ladner, J T; Rozak, D A; Wolcott, M J; Fetterer, D P; Kern, S J; Koroleva, G I; Lovett, S P; Palacios, G F; Toothman, R G; Bozue, J A; Worsham, P L; Welkos, S L

2017-01-01

Burkholderia pseudomallei (Bp), the agent of melioidosis, causes disease ranging from acute and rapidly fatal to protracted and chronic. Bp is highly infectious by aerosol, can cause severe disease with nonspecific symptoms, and is naturally resistant to multiple antibiotics. However, no vaccine exists. Unlike many Bp strains, which exhibit random variability in traits such as colony morphology, Bp strain MSHR5848 exhibited two distinct and relatively stable colony morphologies on sheep blood agar plates: a smooth, glossy, pale yellow colony and a flat, rough, white colony. Passage of the two variants, designated "Smooth" and "Rough", under standard laboratory conditions produced cultures composed of > 99.9% of the single corresponding type; however, both could switch to the other type at different frequencies when incubated in certain nutritionally stringent or stressful growth conditions. These MSHR5848 derivatives were extensively characterized to identify variant-associated differences. Microscopic and colony morphology differences on six differential media were observed and only the Rough variant metabolized sugars in selective agar. Antimicrobial susceptibilities and lipopolysaccharide (LPS) features were characterized and phenotype microarray profiles revealed distinct metabolic and susceptibility disparities between the variants. Results using the phenotype microarray system narrowed the 1,920 substrates to a subset which differentiated the two variants. Smooth grew more rapidly in vitro than Rough, yet the latter exhibited a nearly 10-fold lower lethal dose for mice than Smooth. Finally, the Smooth variant was phagocytosed and replicated to a greater extent and was more cytotoxic than Rough in macrophages. In contrast, multiple locus sequence type (MLST) analysis, ribotyping, and whole genome sequence analysis demonstrated the variants' genetic conservation; only a single consistent genetic difference between the two was identified for further study. These distinct differences shown by two variants of a Bp strain will be leveraged to better understand the mechanism of Bp phenotypic variability and to possibly identify in vitro markers of infection.

Microarray and FISH-based genotype-phenotype analysis of 22 Japanese patients with Wolf-Hirschhorn syndrome.

PubMed

Shimizu, Kenji; Wakui, Keiko; Kosho, Tomoki; Okamoto, Nobuhiko; Mizuno, Seiji; Itomi, Kazuya; Hattori, Shigeto; Nishio, Kimio; Samura, Osamu; Kobayashi, Yoshiyuki; Kako, Yuko; Arai, Takashi; Tsutomu, Oh-ishi; Kawame, Hiroshi; Narumi, Yoko; Ohashi, Hirofumi; Fukushima, Yoshimitsu

2014-03-01

Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome of the distal 4p chromosome, characterized by craniofacial features, growth impairment, intellectual disability, and seizures. Although genotype-phenotype correlation studies have previously been published, several important issues remain to be elucidated including seizure severity. We present detailed clinical and molecular-cytogenetic findings from a microarray and fluorescence in situ hybridization (FISH)-based genotype-phenotype analysis of 22 Japanese WHS patients, the first large non-Western series. 4p deletions were terminal in 20 patients and interstitial in two, with deletion sizes ranging from 2.06 to 29.42 Mb. The new Wolf-Hirschhorn syndrome critical region (WHSCR2) was deleted in all cases, and duplication of other chromosomal regions occurred in four. Complex mosaicism was identified in two cases: two different 4p terminal deletions; a simple 4p terminal deletion and an unbalanced translocation with the same 4p breakpoint. Seizures began in infancy in 33% (2/6) of cases with small (<6 Mb) deletions and in 86% (12/14) of cases with larger deletions (>6 Mb). Status epilepticus occurred in 17% (1/6) with small deletions and in 87% (13/15) with larger deletions. Renal hypoplasia or dysplasia and structural ocular anomalies were more prevalent in those with larger deletions. A new susceptible region for seizure occurrence is suggested between 0.76 and 1.3 Mb from 4 pter, encompassing CTBP1 and CPLX1, and distal to the previously-supposed candidate gene LETM1. The usefulness of bromide therapy for seizures and additional clinical features including hypercholesterolemia are also described. © 2013 Wiley Periodicals, Inc.

Perimysial fibroblasts of extraocular muscle, as unique as the muscle fibers.

PubMed

Kusner, Linda L; Young, Andrew; Tjoe, Steven; Leahy, Patrick; Kaminski, Henry J

2010-01-01

Extraocular muscle (EOM) has a distinct skeletal muscle phenotype. The hypothesis for the study was that fibroblasts support the unique EOM phenotype and that perimysial fibroblasts derived from EOM have properties that distinguish them from fibroblasts derived from other skeletal muscle. Perimysial fibroblasts from leg muscle (LM-Fibro) and EOM (EOM-Fibro) of mice were derived and maintained in culture. EOM- and LM-Fibro were assessed morphologically and for vimentin, smooth muscle actin, and Thy-1 immunoreactivity. DNA microarray analysis was performed on LM- and EOM-Fibro grown in conditions that support myoblast differentiation. To assess trophic interactions, co-cultures of myoblasts from established cell lines, CL-EOM and CL-LM with, EOM- or LM-Fibro were performed in direct contact and in a permeable filter support culture. The degree of myotube maturation was assessed by the percentage of myotubes with more than three myonuclei per myotube. EOM- and LM-Fibro cells exhibited distinct morphologies. Both cell types proliferated as a monolayer and expressed vimentin. Fifty-five percent (SD 4.4%) of EOM-Fibro were Thy-1 positive compared with only 24% (SD 4.4%) of LM-Fibro. DNA microarray analysis demonstrated differential expression of structural, immune response, and metabolism-related genes between EOM- and LM-Fibro. Co-cultures demonstrated that mature myotube formation in EOM-derived cell lines was supported to a greater extent by EOM-Fibro than by LM-Fibro, compared with CL-EOM grown with LM-Fibro. Fibroblasts from EOM demonstrate distinct properties that distinguish them from leg muscle-derived fibroblasts. The distinct properties of EOM-Fibro may support the unique EOM phenotype and contribute to their differential involvement in disease.

Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon

PubMed Central

Wilson, James W.; Ramamurthy, Rajee; Porwollik, Steffen; McClelland, Michael; Hammond, Timothy; Allen, Pat; Ott, C. Mark; Pierson, Duane L.; Nickerson, Cheryl A.

2002-01-01

The low-shear environment of optimized rotation suspension culture allows both eukaryotic and prokaryotic cells to assume physiologically relevant phenotypes that have led to significant advances in fundamental investigations of medical and biological importance. This culture environment has also been used to model microgravity for ground-based studies regarding the impact of space flight on eukaryotic and prokaryotic physiology. We have previously demonstrated that low-shear modeled microgravity (LSMMG) under optimized rotation suspension culture is a novel environmental signal that regulates the virulence, stress resistance, and protein expression levels of Salmonella enterica serovar Typhimurium. However, the mechanisms used by the cells of any species, including Salmonella, to sense and respond to LSMMG and identities of the genes involved are unknown. In this study, we used DNA microarrays to elucidate the global transcriptional response of Salmonella to LSMMG. When compared with identical growth conditions under normal gravity (1 × g), LSMMG differentially regulated the expression of 163 genes distributed throughout the chromosome, representing functionally diverse groups including transcriptional regulators, virulence factors, lipopolysaccharide biosynthetic enzymes, iron-utilization enzymes, and proteins of unknown function. Many of the LSMMG-regulated genes were organized in clusters or operons. The microarray results were further validated by RT-PCR and phenotypic analyses, and they indicate that the ferric uptake regulator is involved in the LSMMG response. The results provide important insight about the Salmonella LSMMG response and could provide clues for the functioning of known Salmonella virulence systems or the identification of uncharacterized bacterial virulence strategies. PMID:12370447

PGMapper: a web-based tool linking phenotype to genes.

PubMed

Xiong, Qing; Qiu, Yuhui; Gu, Weikuan

2008-04-01

With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species. Available online at http://www.genediscovery.org/pgmapper/index.jsp.

Genome‐wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders

PubMed Central

Coleman, Jonathan R.I.; Lester, Kathryn J.; Keers, Robert; Munafò, Marcus R.; Breen, Gerome

2017-01-01

Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight‐year‐old participants (n = 4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non‐Verbal Accuracy (DANVA) faces test. Genome‐wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome‐wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP‐chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non‐zero estimates of SNP‐heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype. PMID:28608620

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

Analysis of the miRNA Profiles of Melanoma Exosomes Derived Under Normoxic and Hypoxic Culture Conditions.

PubMed

Wozniak, Michal; Peczek, Lukasz; Czernek, Liliana; Düchler, Markus

2017-12-01

MicroRNAs (miRNAs) transported in melanoma-derived exosomes function as intercellular messengers supporting tumor survival and progression. Hypoxia increases melanoma phenotypic plasticity, drug resistance, and metastasis. We determined the miRNA profiles in exosomes derived from melanoma cells grown under hypoxic and normoxic conditions by microarray analyses and reverse transcription-polymerase chain reaction (RT-PCR) in order to analyze the potential influence of vesicle-transported miRNAs on cancer-related pathways and transcriptional programs. Despite phenotypical differences of the four cell lines used, their exosomes shared the majority of miRNAs. The levels of three miRNAs were higher in normoxic exosomes, whereas 15 miRNAs were significantly more abundant under hypoxic conditions. Pathway analysis pointed at several cellular processes contributing to proliferation, drug resistance, and modification of the tumor microenvironment, including immunosuppression. The miRNA-expression profiles of exosomes from patient-derived melanoma cells are modified by oxygen concentration and reflect the phenotypic changes of melanoma cells under different growth conditions. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Chromosomal microarray analysis of Bulgarian patients with epilepsy and intellectual disability.

PubMed

Peycheva, Valentina; Kamenarova, Kunka; Ivanova, Neviana; Stamatov, Dimitar; Avdjieva-Tzavella, Daniela; Alexandrova, Iliana; Zhelyazkova, Sashka; Pacheva, Iliana; Dimova, Petya; Ivanov, Ivan; Litvinenko, Ivan; Bozhinova, Veneta; Tournev, Ivailo; Simeonov, Emil; Mitev, Vanyo; Jordanova, Albena; Kaneva, Radka

2018-08-15

High resolution chromosomal microarray analysis (CMA) has facilitated the identification of small chromosomal rearrangements throughout the genome, associated with various neurodevelopmental phenotypes, including ID/DD. Recently, it became evident that intellectual disability (ID)/developmental delay (DD) can occur with associated co-morbidities like epileptic seizures, autism and additional congenital anomalies. These observations require whole genome approach in order to detect the genetic causes of these complex disorders. In this study, we examined 92 patients of Bulgarian origin at age between 1 and 22 years with ID, generalized epilepsy, autistic signs and congenital anomalies. CMA was carried out using SurePrint G3 Human CGH Microarray Kit, 4 × 180 K and SurePrint G3 Unrestricted CGH ISCA v2, 4 × 180 K oligo platforms. Referral indications for selection of the patients were the presence of generalized refractory seizures disorders and co-morbid ID. Clearly pathogenic copy number variations (CNVs) were detected in eight patients (8.7%) from our cohort. Additionally, possibly pathogenic rearrangements of unclear clinical significance were detected in six individuals (6.5%), which make for an overall diagnostic yield of 15.2% among our cohort of patients. We report here the patients with clearly pathogenic CNVs, discuss the potential causality of the possibly pathogenic CNVs and make genotype - phenotype correlations. One novel possibly pathogenic heterozygous deletion in 15q22.31 region was detected in a case with ID/DD. Additionally, whole APBA2 gene duplication in 15q13.1 was found in three generations of a family with epilepsy, ID and psychiatric abnormalities. The results from this study allow us to define the genetic diagnosis in a subset of Bulgarian patients and improve the genetic counseling of the affected families. To our knowledge, this is the first aCGH evaluation of a Bulgarian cohort of children with epilepsy and ID so far. Copyright © 2018 Elsevier B.V. All rights reserved.

Coordinated transcriptional regulation patterns associated with infertility phenotypes in men

PubMed Central

Ellis, Peter J I; Furlong, Robert A; Conner, Sarah J; Kirkman‐Brown, Jackson; Afnan, Masoud; Barratt, Christopher; Griffin, Darren K; Affara, Nabeel A

2007-01-01

Introduction Microarray gene‐expression profiling is a powerful tool for global analysis of the transcriptional consequences of disease phenotypes. Understanding the genetic correlates of particular pathological states is important for more accurate diagnosis and screening of patients, and thus for suggesting appropriate avenues of treatment. As yet, there has been little research describing gene‐expression profiling of infertile and subfertile men, and thus the underlying transcriptional events involved in loss of spermatogenesis remain unclear. Here we present the results of an initial screen of 33 patients with differing spermatogenic phenotypes. Methods Oligonucleotide array expression profiling was performed on testis biopsies for 33 patients presenting for testicular sperm extraction. Significantly regulated genes were selected using a mixed model analysis of variance. Principle components analysis and hierarchical clustering were used to interpret the resulting dataset with reference to the patient history, clinical findings and histological composition of the biopsies. Results Striking patterns of coordinated gene expression were found. The most significant contains multiple germ cell‐specific genes and corresponds to the degree of successful spermatogenesis in each patient, whereas a second pattern corresponds to inflammatory activity within the testis. Smaller‐scale patterns were also observed, relating to unique features of the individual biopsies. PMID:17496197

Gene expression and the biological phenotype of papillary thyroid carcinomas.

PubMed

Delys, L; Detours, V; Franc, B; Thomas, G; Bogdanova, T; Tronko, M; Libert, F; Dumont, J E; Maenhaut, C

2007-12-13

The purpose of this paper is to correlate the molecular phenotype of papillary thyroid carcinoma (PTC) to their biological pathology. We hybridized 26 PTC on microarrays and showed that nearly 44% of the transcriptome was regulated in these tumors. We then combined our data set with two published PTC microarray studies to produce a platform- and study-independent list of PTC-associated genes. We further confirmed the mRNA regulation of 15 genes from this list by quantitative reverse transcription-PCR. Analysis of this list with statistical tools led to several conclusions: (1) there is a change in cell population with an increased expression of genes involved in the immune response, reflecting lymphocyte infiltration in the tumor compared to the normal tissue. (2) The c-jun N-terminal kinase pathway is activated by overexpression of its components. (3) The activation of ERKK1/2 by genetic alterations is supplemented by activation of the epidermal growth factor but not of the insulin-like growth factor signaling pathway. (4) There is a downregulation of immediate early genes. (5) We observed an overexpression of many proteases in accordance with tumor remodeling, and suggested a probable role of S100 proteins and annexin A2 in this process. (6) Numerous overexpressed genes favor the hypothesis of a collective migration mode of tumor cells.

Uniparental Disomy of Chromosome 15 in Two Cases by Chromosome Microarray: A Lesson Worth Thinking.

PubMed

Liu, Shu; Zhang, Kaihui; Song, Fengling; Yang, Yali; Lv, Yuqiang; Gao, Min; Liu, Yi; Gai, Zhongtao

2017-01-01

Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurogenetic disorders caused by loss of function of the imprinted genes at 15q11q13. A 5-7 Mb paternal/maternal deletion of chromosomal region 15q11.2q13 is the major genetic cause of PWS/AS, but in a small group of patients, the PWS/AS phenotype can result from maternal/paternal uniparental disomy (UPD) of chromosome 15. Various mechanisms leading to UPD include gametic complementation, trisomy rescue, and compensatory UPD, which can be inferred from the pattern of uniparental heterodisomy (heteroUPD) or uniparental isodisomy (isoUPD). However, heteroUPD and isoUPD, especially mixed heteroUPD and isoUPD, are very rare in patients with PWS/AS. Here, we report 2 children with PWS/AS caused by mixed segmental heteroUPD 15 and isoUPD 15 which failed to be identified by chromosome microarray (CMA) but could be detected by other molecular genetic methods. The present report unravels the mechanism of mixed iso/heteroUPD 15 in PWS/AS and phenotype-genotype correlations. Moreover, our study suggests that CMA is prone to misdiagnosis for imprinting disorders such as PWS/AS, though it is considered a highly useful tool for copy number variations. As a result, other molecular detection methods, such as methylation analysis and STR marker analysis for UPD, should be supplementary used in this situation. © 2017 S. Karger AG, Basel.

Stable phenotype of B-cell subsets following cryopreservation and thawing of normal human lymphocytes stored in a tissue biobank.

PubMed

Rasmussen, Simon Mylius; Bilgrau, Anders Ellern; Schmitz, Alexander; Falgreen, Steffen; Bergkvist, Kim Steve; Tramm, Anette Mai; Baech, John; Jacobsen, Chris Ladefoged; Gaihede, Michael; Kjeldsen, Malene Krag; Bødker, Julie Støve; Dybkaer, Karen; Bøgsted, Martin; Johnsen, Hans Erik

2015-01-01

Cryopreservation is an acknowledged procedure to store vital cells for future biomarker analyses. Few studies, however, have analyzed the impact of the cryopreservation on phenotyping. We have performed a controlled comparison of cryopreserved and fresh cellular aliquots prepared from individual healthy donors. We studied circulating B-cell subset membrane markers and global gene expression, respectively by multiparametric flow cytometry and microarray data. Extensive statistical analysis of the generated data tested the concept that "overall, there are no phenotypic differences between cryopreserved and fresh B-cell subsets." Subsequently, we performed an uncontrolled comparison of tonsil tissue samples. By multiparametric flow analysis, we documented no significant changes following cryopreservation of subset frequencies or membrane intensity for the differentiation markers CD19, CD20, CD22, CD27, CD38, CD45, and CD200. By gene expression profiling following cryopreservation, across all samples, only 16 out of 18708 genes were significantly up or down regulated, including FOSB, KLF4, RBP7, ANXA1 or CLC, DEFA3, respectively. Implementation of cryopreserved tissue in our research program allowed us to present a performance analysis, by comparing cryopreserved and fresh tonsil tissue. As expected, phenotypic differences were identified, but to an extent that did not affect the performance of the cryopreserved tissue to generate specific B-cell subset associated gene signatures and assign subset phenotypes to independent tissue samples. We have confirmed our working concept and illustrated the usefulness of vital cryopreserved cell suspensions for phenotypic studies of the normal B-cell hierarchy; however, storage procedures need to be delineated by tissue-specific comparative analysis. © 2014 Clinical Cytometry Society.

Stable Phenotype Of B-Cell Subsets Following Cryopreservation and Thawing of Normal Human Lymphocytes Stored in a Tissue Biobank.

PubMed

Rasmussen, Simon Mylius; Bilgrau, Anders Ellern; Schmitz, Alexander; Falgreen, Steffen; Bergkvist, Kim Steve; Tramm, Anette Mai; Baech, John; Jacobsen, Chris Ladefoged; Gaihede, Michael; Kjeldsen, Malene Krag; Bødker, Julie Støve; Dybkaer, Karen; Bøgsted, Martin; Johnsen, Hans Erik

2014-09-20

Background Cryopreservation is an acknowledged procedure to store vital cells for future biomarker analyses. Few studies, however, have analyzed the impact of the cryopreservation on phenotyping. Methods We have performed a controlled comparison of cryopreserved and fresh cellular aliquots prepared from individual healthy donors. We studied circulating B-cell subset membrane markers and global gene expression, respectively by multiparametric flow cytometry and microarray data. Extensive statistical analysis of the generated data tested the concept that "overall, there are phenotypic differences between cryopreserved and fresh B-cell subsets". Subsequently, we performed a consecutive uncontrolled comparison of tonsil tissue samples. Results By multiparametric flow analysis, we documented no significant changes following cryopreservation of subset frequencies or membrane intensity for the differentiation markers CD19, CD20, CD22, CD27, CD38, CD45, and CD200. By gene expression profiling following cryopreservation, across all samples, only 16 out of 18708 genes were significantly up or down regulated, including FOSB, KLF4, RBP7, ANXA1 or CLC, DEFA3, respectively. Implementation of cryopreserved tissue in our research program allowed us to present a performance analysis, by comparing cryopreserved and fresh tonsil tissue. As expected, phenotypic differences were identified, but to an extent that did not affect the performance of the cryopreserved tissue to generate specific B-cell subset associated gene signatures and assign subset phenotypes to independent tissue samples. Conclusions We have confirmed our working concept and illustrated the usefulness of vital cryopreserved cell suspensions for phenotypic studies of the normal B-cell hierarchy; however, storage procedures need to be delineated by tissue specific comparative analysis. © 2014 Clinical Cytometry Society. Copyright © 2014 Clinical Cytometry Society.

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.

Prenatal diagnosis of two fetuses with deletions of 8p23.1, critical region for congenital diaphragmatic hernia and heart defects.

PubMed

Keitges, Elisabeth A; Pasion, Romela; Burnside, Rachel D; Mason, Carla; Gonzalez-Ruiz, Antonio; Dunn, Teresa; Masiello, Meredith; Gebbia, Joseph A; Fernandez, Carlos O; Risheg, Hiba

2013-07-01

Microdeletions of 8p23.1 are mediated by low copy repeats and can cause congenital diaphragmatic hernia (CDH) and cardiac defects. Within this region, point mutations of the GATA4 gene have been shown to cause cardiac defects. However, the cause of CDH in these deletions has been difficult to determine due to the paucity of mutations that result in CDH, the lack of smaller deletions to refine the region and the reduced penetrance of CDH in these large deletions. Mice deficient for one copy of the Gata4 gene have been described with CDH and heart defects suggesting mutations in Gata4 can cause the phenotype in mice. We report on the SNP microarray analysis on two fetuses with deletions of 8p23.1. The first had CDH and a ventricular septal defect (VSD) on ultrasonography and a family history of a maternal VSD. Microarray analysis detected a 127-kb deletion which included the GATA4 and NEIL2 genes which was inherited from the mother. The second fetus had an incomplete atrioventricular canal defect on ultrasonography. Microarray analysis showed a 315-kb deletion that included seven genes, GATA4, NEIL2, FDFT1, CTSB, DEFB136, DEFB135, and DEFB134. These results suggest that haploinsufficiency of the two genes in common within 8p23.1; GATA4 and NEIL2 can cause CDH and cardiac defects in humans. Copyright © 2013 Wiley Periodicals, Inc.

Profiling protein function with small molecule microarrays

PubMed Central

Winssinger, Nicolas; Ficarro, Scott; Schultz, Peter G.; Harris, Jennifer L.

2002-01-01

The regulation of protein function through posttranslational modification, local environment, and protein–protein interaction is critical to cellular function. The ability to analyze on a genome-wide scale protein functional activity rather than changes in protein abundance or structure would provide important new insights into complex biological processes. Herein, we report the application of a spatially addressable small molecule microarray to an activity-based profile of proteases in crude cell lysates. The potential of this small molecule-based profiling technology is demonstrated by the detection of caspase activation upon induction of apoptosis, characterization of the activated caspase, and inhibition of the caspase-executed apoptotic phenotype using the small molecule inhibitor identified in the microarray-based profile. PMID:12167675

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

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

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

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

PubMed

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

2012-06-08

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

Selection and phenotypic characterization of a core collection of Brachypodium distachyon inbred lines.

PubMed

Tyler, Ludmila; Fangel, Jonatan U; Fagerström, Alexandra Dotson; Steinwand, Michael A; Raab, Theodore K; Willats, William Gt; Vogel, John P

2014-01-14

The model grass Brachypodium distachyon is increasingly used to study various aspects of grass biology. A large and genotypically diverse collection of B. distachyon germplasm has been assembled by the research community. The natural variation in this collection can serve as a powerful experimental tool for many areas of inquiry, including investigating biomass traits. We surveyed the phenotypic diversity in a large collection of inbred lines and then selected a core collection of lines for more detailed analysis with an emphasis on traits relevant to the use of grasses as biofuel and grain crops. Phenotypic characters examined included plant height, growth habit, stem density, flowering time, and seed weight. We also surveyed differences in cell wall composition using near infrared spectroscopy (NIR) and comprehensive microarray polymer profiling (CoMPP). In all cases, we observed extensive natural variation including a two-fold variation in stem density, four-fold variation in ferulic acid bound to hemicellulose, and 1.7-fold variation in seed mass. These characterizations can provide the criteria for selecting diverse lines for future investigations of the genetic basis of the observed phenotypic variation.

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH

PubMed Central

2009-01-01

Background Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. Results We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. Conclusion The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies. PMID:19925645

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

PubMed Central

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

2011-01-01

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

An experimental loop design for the detection of constitutional chromosomal aberrations by array CGH.

PubMed

Allemeersch, Joke; Van Vooren, Steven; Hannes, Femke; De Moor, Bart; Vermeesch, Joris Robert; Moreau, Yves

2009-11-19

Comparative genomic hybridization microarrays for the detection of constitutional chromosomal aberrations is the application of microarray technology coming fastest into routine clinical application. Through genotype-phenotype association, it is also an important technique towards the discovery of disease causing genes and genomewide functional annotation in human. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient against a normal reference sample. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the "normal" reference instead of a patient aberration. Instead, we apply an experimental loop design that compares three patients in three hybridizations. We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of 27 patients seen at our genetics center, we observed that the linear models of the log ratios are advantageous over the mixed models of the absolute intensities. The loop design and the performance of the statistical analysis contribute to the quick adoption of array CGH as a routine diagnostic tool. They lower the detection limit of mosaicisms and improve the assignment of copy number variation for genetic association studies.

Role of Arabidopsis ABF1/3/4 during det1 germination in salt and osmotic stress conditions.

PubMed

Fernando, V C Dilukshi; Al Khateeb, Wesam; Belmonte, Mark F; Schroeder, Dana F

2018-05-01

Arabidopsis det1 mutants exhibit salt and osmotic stress resistant germination. This phenotype requires HY5, ABF1, ABF3, and ABF4. While DE-ETIOLATED 1 (DET1) is well known as a negative regulator of light development, here we describe how det1 mutants also exhibit altered responses to salt and osmotic stress, specifically salt and mannitol resistant germination. LONG HYPOCOTYL 5 (HY5) positively regulates both light and abscisic acid (ABA) signalling. We found that hy5 suppressed the det1 salt and mannitol resistant germination phenotype, thus, det1 stress resistant germination requires HY5. We then queried publically available microarray datasets to identify genes downstream of HY5 that were differentially expressed in det1 mutants. Our analysis revealed that ABA regulated genes, including ABA RESPONSIVE ELEMENT BINDING FACTOR 3 (ABF3), are downregulated in det1 seedlings. We found that ABF3 is induced by salt in wildtype seeds, while homologues ABF4 and ABF1 are repressed, and all three genes are underexpressed in det1 seeds. We then investigated the role of ABF3, ABF4, and ABF1 in det1 phenotypes. Double mutant analysis showed that abf3, abf4, and abf1 all suppress the det1 salt/osmotic stress resistant germination phenotype. In addition, abf1 suppressed det1 rapid water loss and open stomata phenotypes. Thus interactions between ABF genes contribute to det1 salt/osmotic stress response phenotypes.

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

Novel contiguous gene deletion in peruvian girl with Trichothiodystrophy type 4 and glutaric aciduria type 3.

PubMed

La Serna-Infantes, Jorge; Pastor, Miguel Chávez; Trubnykova, Milana; Velásquez, Félix Chavesta; Sotomayor, Flor Vásquez; Barriga, Hugo Abarca

2018-07-01

Trichothiodystrophy type 4 is a rare autosomal recessive and ectodermal disorder, characterized by dry, brittle, sparse and sulfur-deficient hair and other features like intellectual disability, ichthyotic skin and short stature, caused by a homozygous mutation in MPLKIP gene. Glutaric aciduria type 3 is caused by a homozygous mutation in SUGCT gene with no distinctive phenotype. Both genes are localized on chromosome 7 (7p14). We report an 8-year-old female with short stature, microcephaly, development delay, intellectual disability and hair characterized for dark, short, coarse, sparse and brittle associated to classical trichorrhexis microscopy pattern. Chromosome microarray analysis showed a 125 kb homozygous pathogenic deletion, which includes genes MPLKIP and SUGCT, not described before. This is the first case described in Peru of a novel contiguous gene deletion of Trichothiodystrophy type 4 and Glutaric aciduria type 3 performed by chromosome microarray analysis, highlighting the contribution and importance of molecular technologies on diagnosis of rare genetic conditions. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Clinical comparison of overlapping deletions of 19p13.3.

PubMed

Risheg, Hiba; Pasion, Romela; Sacharow, Stephanie; Proud, Virginia; Immken, LaDonna; Schwartz, Stuart; Tepperberg, Jim H; Papenhausen, Peter; Tan, Tiong Y; Andrieux, Joris; Plessis, Ghislaine; Amor, David J; Keitges, Elisabeth A

2013-05-01

We present three patients with overlapping interstitial deletions of 19p13.3 identified by high resolution SNP microarray analysis. All three had a similar phenotype characterized by intellectual disability or developmental delay, structural heart abnormalities, large head relative to height and weight or macrocephaly, and minor facial anomalies. Deletion sizes ranged from 792 Kb to 1.0 Mb and included a common region arr [hg19] 19p13.3 (3,814,392-4,136,989), containing eight genes: ZFR2, ATCAY, NMRK2, DAPK3, EEF2, PIAS4, ZBTB7A, MAP2K2, and two non-coding RNA's MIR637 and SNORDU37. The patient phenotypes were compared with three previous single patient reports with similar interstitial 19p13.3 deletions and six additional patients from the DECIPHER and ISCA databases to determine if a common haploinsufficient phenotype for the region can be established. Copyright © 2013 Wiley Periodicals, Inc.

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

NASA Technical Reports Server (NTRS)

Weitzeal, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

2016-01-01

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASAs GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-boxkelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASAs VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

NASA Technical Reports Server (NTRS)

Weitzeal, A. J.; Wyatt, S. E.; Parsons-Wingerter, P.

2016-01-01

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Diagnosis of Familial Wolf-Hirschhorn Syndrome due to a Paternal Cryptic Chromosomal Rearrangement by Conventional and Molecular Cytogenetic Techniques

PubMed Central

Venegas-Vega, Carlos A.; Zepeda, Luis M.; Garduño-Zarazúa, Luz M.; Berumen, Jaime; Kofman, Susana; Cervantes, Alicia

2013-01-01

The use of conventional cytogenetic techniques in combination with fluorescent in situ hybridization (FISH) and single-nucleotide polymorphism (SNP) microarrays is necessary for the identification of cryptic rearrangements in the diagnosis of chromosomal syndromes. We report two siblings, a boy of 9 years and 9 months of age and his 7-years- and 5-month-old sister, with the classic Wolf-Hirschhorn syndrome (WHS) phenotype. Using high-resolution GTG- and NOR-banding karyotypes, as well as FISH analysis, we characterized a pure 4p deletion in both sibs and a balanced rearrangement in their father, consisting in an insertion of 4p material within a nucleolar organizing region of chromosome 15. Copy number variant (CNV) analysis using SNP arrays showed that both siblings have a similar size of 4p deletion (~6.5 Mb). Our results strongly support the need for conventional cytogenetic and FISH analysis, as well as high-density microarray mapping for the optimal characterization of the genetic imbalance in patients with WHS; parents must always be studied for recognizing cryptic balanced chromosomal rearrangements for an adequate genetic counseling. PMID:23484094

Design of microarray experiments for genetical genomics studies.

PubMed

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

2006-10-01

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

DNA methylation analysis of phenotype specific stratified Indian population.

PubMed

Rotti, Harish; Mallya, Sandeep; Kabekkodu, Shama Prasada; Chakrabarty, Sanjiban; Bhale, Sameer; Bharadwaj, Ramachandra; Bhat, Balakrishna K; Dedge, Amrish P; Dhumal, Vikram Ram; Gangadharan, G G; Gopinath, Puthiya M; Govindaraj, Periyasamy; Joshi, Kalpana S; Kondaiah, Paturu; Nair, Sreekumaran; Nair, S N Venugopalan; Nayak, Jayakrishna; Prasanna, B V; Shintre, Pooja; Sule, Mayura; Thangaraj, Kumarasamy; Patwardhan, Bhushan; Valiathan, Marthanda Varma Sankaran; Satyamoorthy, Kapaettu

2015-05-08

DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

MBD5 haploinsufficiency is associated with sleep disturbance and disrupts circadian pathways common to Smith-Magenis and fragile X syndromes.

PubMed

Mullegama, Sureni V; Pugliesi, Loren; Burns, Brooke; Shah, Zalak; Tahir, Raiha; Gu, Yanghong; Nelson, David L; Elsea, Sarah H

2015-06-01

Individuals with autism spectrum disorders (ASD) who have an identifiable single-gene neurodevelopmental disorder (NDD), such as fragile X syndrome (FXS, FMR1), Smith-Magenis syndrome (SMS, RAI1), or 2q23.1 deletion syndrome (del 2q23.1, MBD5) share phenotypic features, including a high prevalence of sleep disturbance. We describe the circadian deficits in del 2q23.1 through caregiver surveys in which we identify several frequent sleep anomalies, including night/early awakenings, coughing/snoring loudly, and difficulty falling asleep. We couple these findings with studies on the molecular analysis of the circadian deficits associated with haploinsufficiency of MBD5 in which circadian gene mRNA levels of NR1D2, PER1, PER2, and PER3 were altered in del 2q23.1 lymphoblastoid cell lines (LCLs), signifying that haploinsufficiency of MBD5 can result in dysregulation of circadian rhythm gene expression. These findings were further supported by expression microarrays of MBD5 siRNA knockdown cells that showed significantly altered expression of additional circadian rhythm signaling pathway genes. Based on the common sleep phenotypes observed in del 2q23.1, SMS, and FXS patients, we explored the possibility that MBD5, RAI1, and FMR1 function in overlapping circadian rhythm pathways. Bioinformatic analysis identified conserved putative E boxes in MBD5 and RAI1, and expression levels of NR1D2 and CRY2 were significantly reduced in patient LCLs. Circadian and mTOR signaling pathways, both associated with sleep disturbance, were altered in both MBD5 and RAI1 knockdown microarray data, overlapping with findings associated with FMR1. These data support phenotypic and molecular overlaps across these syndromes that may be exploited to provide therapeutic intervention for multiple disorders.

A novel deletion of SNURF/SNRPN exon 1 in a patient with Prader-Willi-like phenotype.

PubMed

Cao, Yang; AlHumaidi, Susan S; Faqeih, Eissa A; Pitel, Beth A; Lundquist, Patrick; Aypar, Umut

2017-08-01

Here we report the smallest deletion involving SNURF/SNRPN that causes major symptoms of Prader-Willi syndrome (PWS), including hypotonia, dysmorphic features, intellectual disability, and obesity. A female patient with the aforementioned and additional features was referred to the Mayo Clinic Cytogenetics laboratory for genetic testing. Chromosomal microarray analysis and subsequent Sanger sequencing identified a de novo 6.4 kb deletion at 15q11.2, containing exon 1 of the SNURF gene and exon 1 of the shortest isoform of the SNRPN gene. SNURF/SNRPN exon 1, which is methylated on the silent maternal allele, is associated with acetylated histones on the expressed paternal allele. This region also overlaps with the PWS-imprinting center (IC). Subsequent molecular methylation analysis was performed using methylation-specific MLPA (MS-MLPA), which characterized that the deletion of SNURF/SNRPN exon 1 was paternal in origin, consistent with the PWS-like phenotype. Since SNURF/SNRPN gene and the PWS-IC are known to regulate snoRNAs, it is likely that the PWS-like phenotype observed in patients with paternal SNURF/SNRPN deletion is due to the disrupted expression of SNORD116 snoRNAs. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

The Cognitive and Behavioral Phenotypes of Individuals with CHRNA7 Duplications.

PubMed

Gillentine, M A; Berry, L N; Goin-Kochel, R P; Ali, M A; Ge, J; Guffey, D; Rosenfeld, J A; Hannig, V; Bader, P; Proud, M; Shinawi, M; Graham, B H; Lin, A; Lalani, S R; Reynolds, J; Chen, M; Grebe, T; Minard, C G; Stankiewicz, P; Beaudet, A L; Schaaf, C P

2017-03-01

Chromosome 15q11q13 is among the least stable regions in the genome due to its highly complex genomic architecture. Low copy repeat elements at 15q13.3 facilitate recurrent copy number variants (CNVs), with deletions established as pathogenic and CHRNA7 implicated as a candidate gene. However, the pathogenicity of duplications of CHRNA7 is unclear, as they are found in affected probands as well as in reportedly healthy parents and unaffected control individuals. We evaluated 18 children with microduplications involving CHRNA7, identified by clinical chromosome microarray analysis (CMA). Comprehensive phenotyping revealed high prevalence of developmental delay/intellectual disability, autism spectrum disorder, and attention deficit/hyperactivity disorder. As CHRNA7 duplications are the most common CNVs identified by clinical CMA, this study provides anticipatory guidance for those involved with care of affected individuals.

The application of artificial intelligence to microarray data: identification of a novel gene signature to identify bladder cancer progression.

PubMed

Catto, James W F; Abbod, Maysam F; Wild, Peter J; Linkens, Derek A; Pilarsky, Christian; Rehman, Ishtiaq; Rosario, Derek J; Denzinger, Stefan; Burger, Maximilian; Stoehr, Robert; Knuechel, Ruth; Hartmann, Arndt; Hamdy, Freddie C

2010-03-01

New methods for identifying bladder cancer (BCa) progression are required. Gene expression microarrays can reveal insights into disease biology and identify novel biomarkers. However, these experiments produce large datasets that are difficult to interpret. To develop a novel method of microarray analysis combining two forms of artificial intelligence (AI): neurofuzzy modelling (NFM) and artificial neural networks (ANN) and validate it in a BCa cohort. We used AI and statistical analyses to identify progression-related genes in a microarray dataset (n=66 tumours, n=2800 genes). The AI-selected genes were then investigated in a second cohort (n=262 tumours) using immunohistochemistry. We compared the accuracy of AI and statistical approaches to identify tumour progression. AI identified 11 progression-associated genes (odds ratio [OR]: 0.70; 95% confidence interval [CI], 0.56-0.87; p=0.0004), and these were more discriminate than genes chosen using statistical analyses (OR: 1.24; 95% CI, 0.96-1.60; p=0.09). The expression of six AI-selected genes (LIG3, FAS, KRT18, ICAM1, DSG2, and BRCA2) was determined using commercial antibodies and successfully identified tumour progression (concordance index: 0.66; log-rank test: p=0.01). AI-selected genes were more discriminate than pathologic criteria at determining progression (Cox multivariate analysis: p=0.01). Limitations include the use of statistical correlation to identify 200 genes for AI analysis and that we did not compare regression identified genes with immunohistochemistry. AI and statistical analyses use different techniques of inference to determine gene-phenotype associations and identify distinct prognostic gene signatures that are equally valid. We have identified a prognostic gene signature whose members reflect a variety of carcinogenic pathways that could identify progression in non-muscle-invasive BCa. 2009 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Honey bee aggression supports a link between gene regulation and behavioral evolution.

PubMed

Alaux, Cédric; Sinha, Saurabh; Hasadsri, Linda; Hunt, Greg J; Guzmán-Novoa, Ernesto; DeGrandi-Hoffman, Gloria; Uribe-Rubio, José Luis; Southey, Bruce R; Rodriguez-Zas, Sandra; Robinson, Gene E

2009-09-08

A prominent theory states that animal phenotypes arise by evolutionary changes in gene regulation, but the extent to which this theory holds true for behavioral evolution is not known. Because "nature and nurture" are now understood to involve hereditary and environmental influences on gene expression, we studied whether environmental influences on a behavioral phenotype, i.e., aggression, could have evolved into inherited differences via changes in gene expression. Here, with microarray analysis of honey bees, we show that aggression-related genes with inherited patterns of brain expression are also environmentally regulated. There were expression differences in the brain for hundreds of genes between the highly aggressive Africanized honey bee compared with European honey bee (EHB) subspecies. Similar results were obtained for EHB in response to exposure to alarm pheromone (which provokes aggression) and when comparing old and young bees (aggressive tendencies increase with age). There was significant overlap of the gene lists generated from these three microarray experiments. Moreover, there was statistical enrichment of several of the same cis regulatory motifs in promoters of genes on all three gene lists. Aggression shows a remarkably robust brain molecular signature regardless of whether it occurs because of inherited, age-related, or environmental (social) factors. It appears that one element in the evolution of different degrees of aggressive behavior in honey bees involved changes in regulation of genes that mediate the response to alarm pheromone.

Association of a homozygous nonsense mutation in the ABCA4 (ABCR) gene with cone-rod dystrophy phenotype in an Italian family.

PubMed

Simonelli, Francesca; Testa, Francesco; Zernant, Jana; Nesti, Anna; Rossi, Settimio; Rinaldi, Ernesto; Allikmets, Rando

2004-01-01

Genetic variation in the ABCA4 (ABCR) gene has been associated with several distinct retinal phenotypes, including Stargardt disease/fundus flavimaculatus (STGD/FFM), cone-rod dystrophy (CRD), retinitis pigmentosa (RP) and age-related macular degeneration. The current model of genotype/phenotype association suggests that patients harboring deleterious mutations in both ABCR alleles would develop RP-like retinal pathology. Here we describe ABCA4-associated phenotypes, including a proband with a homozygous nonsense mutation in a family from Southern Italy. The proband had been originally diagnosed with STGD. Ophthalmologic examination included kinetic perimetry, electrophysiological studies and fluorescein angiography. DNA of the affected individual and family members was analyzed for variants in all 50 exons of the ABCA4 gene by screening on the ABCR400 microarray. A homozygous nonsense mutation 2971G>T (G991X) was detected in a patient initially diagnosed with STGD based on funduscopic evidence, including bull's eye depigmentation of the fovea and flecks at the posterior pole extending to the mid-peripheral retina. Since this novel nucleotide substitution results in a truncated, nonfunctional, ABCA4 protein, the patient was examined in-depth for the severity of the disease phenotype. Indeed, subsequent electrophysiological studies determined severely reduced cone amplitude as compared to the rod amplitude, suggesting the diagnosis of CRD. ABCR400 microarray is an efficient tool for determining causal genetic variation, including new mutations. A homozygous protein-truncating mutation in ABCA4 can cause a phenotype ranging from STGD to CRD as diagnosed at an early stage of the disease. Only a combination of comprehensive genotype/phenotype correlation studies will determine the proper diagnosis and prognosis of ABCA4-associated pathology. Copyright 2004 S. Karger AG, Basel

Complete genome sequence and phenotype microarray analysis of Cronobacter sakazakii SP291: a persistent isolate cultured from a powdered infant formula production facility.

PubMed

Yan, Qiongqiong; Power, Karen A; Cooney, Shane; Fox, Edward; Gopinath, Gopal R; Grim, Christopher J; Tall, Ben D; McCusker, Matthew P; Fanning, Séamus

2013-01-01

Outbreaks of human infection linked to the powdered infant formula (PIF) food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC) and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC)], pSP291-2, [52.1-kb (49.2% GC)], and pSP291-3, [4.4-kb (54.0% GC)]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM), we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment.

Complete genome sequence and phenotype microarray analysis of Cronobacter sakazakii SP291: a persistent isolate cultured from a powdered infant formula production facility

PubMed Central

Yan, Qiongqiong; Power, Karen A.; Cooney, Shane; Fox, Edward; Gopinath, Gopal R.; Grim, Christopher J.; Tall, Ben D.; McCusker, Matthew P.; Fanning, Séamus

2013-01-01

Outbreaks of human infection linked to the powdered infant formula (PIF) food chain and associated with the bacterium Cronobacter, are of concern to public health. These bacteria are regarded as opportunistic pathogens linked to life-threatening infections predominantly in neonates, with an under developed immune system. Monitoring the microbiological ecology of PIF production sites is an important step in attempting to limit the risk of contamination in the finished food product. Cronobacter species, like other microorganisms can adapt to the production environment. These organisms are known for their desiccation tolerance, a phenotype that can aid their survival in the production site and PIF itself. In evaluating the genome data currently available for Cronobacter species, no sequence information has been published describing a Cronobacter sakazakii isolate found to persist in a PIF production facility. Here we report on the complete genome sequence of one such isolate, Cronobacter sakazakii SP291 along with its phenotypic characteristics. The genome of C. sakazakii SP291 consists of a 4.3-Mb chromosome (56.9% GC) and three plasmids, denoted as pSP291-1, [118.1-kb (57.2% GC)], pSP291-2, [52.1-kb (49.2% GC)], and pSP291-3, [4.4-kb (54.0% GC)]. When C. sakazakii SP291 was compared to the reference C. sakazakii ATCC BAA-894, which is also of PIF origin, the annotated genome data identified two interesting functional categories, comprising of genes related to the bacterial stress response and resistance to antimicrobial and toxic compounds. Using a phenotypic microarray (PM), we provided a full metabolic profile comparing C. sakazakii SP291 and the previously sequenced C. sakazakii ATCC BAA-894. These data extend our understanding of the genome of this important neonatal pathogen and provides further insights into the genotypes associated with features that can contribute to its persistence in the PIF environment. PMID:24032028

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

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

Metabolic parameters linked by phenotype microarray to acid resistance profiles of poultry-associated Salmonella enterica.

PubMed

Guard, Jean; Rothrock, Michael J; Shah, Devendra H; Jones, Deana R; Gast, Richard K; Sanchez-Ingunza, Roxana; Madsen, Melissa; El-Attrache, John; Lungu, Bwalya

Phenotype microarrays were analyzed for 51 datasets derived from Salmonella enterica. The top 4 serotypes associated with poultry products and one associated with turkey, respectively Typhimurium, Enteritidis, Heidelberg, Infantis and Senftenberg, were represented. Datasets were partitioned initially into two clusters based on ranking by values at pH 4.5 (PM10 A03). Negative control wells were used to establish 90 respiratory units as the point differentiating acid resistance from sensitive strains. Thus, 24 isolates that appeared most acid-resistant were compared initially to 27 that appeared most acid-sensitive (24 × 27 format). Paired cluster analysis was also done and it included the 7 most acid-resistant and -sensitive datasets (7 × 7 format). Statistical analyses of ranked data were then calculated in order of standard deviation, probability value by the Student's t-test and a measure of the magnitude of difference called effect size. Data were reported as significant if, by order of filtering, the following parameters were calculated: i) a standard deviation of 24 respiratory units or greater from all datasets for each chemical, ii) a probability value of less than or equal to 0.03 between clusters and iii) an effect size of at least 0.50 or greater between clusters. Results suggest that between 7.89% and 23.16% of 950 chemicals differentiated acid-resistant isolates from sensitive ones, depending on the format applied. Differences were more evident at the extremes of phenotype using the subset of data in the paired 7 × 7 format. Results thus provide a strategy for selecting compounds for additional research, which may impede the emergence of acid-resistant Salmonella enterica in food. Published by Elsevier Masson SAS.

Downstream effects of ROCK signaling in cultured human corneal stromal cells: microarray analysis of gene expression.

PubMed

Harvey, Stephen A K; Anderson, Susan C; SundarRaj, Nirmala

2004-07-01

Rho-associated coiled-coil-containing protein kinase (ROCK) is a downstream target of Rho GTPase signaling and regulates the assembly of stress fibers. Previous reports indicate that Rho/ROCK signaling is involved in the regulation of several cellular processes, some of which may be cell-type specific and are probably critical to corneal stromal cell activation. The present study identified ROCK-regulated gene expression in corneal stromal cells. Corneal stromal cells derived from eyes of three different donors were cultured to yield the following designated phenotypes: baseline fibroblasts (DMEM with 10% serum), activated fibroblasts (10% serum+bFGF+heparin), and myofibroblasts (1% serum+TGF-beta 1). Cells were exposed to the ROCK inhibitor Y-27632 or vehicle for 12 hours, and transcript levels altered by ROCK inhibition were identified with oligonucleotide microarrays (GeneChips; Affymetrix, Santa Clara, CA). In these phenotypes, Y-27632 caused marked (twofold or more) increases or decreases in 14/4, 12/3, and 15/10 transcripts. In both fibroblast groups Y-27632-treatment increased expression of endothelin receptors and of parathyroid hormone-like hormone. The upregulation of alpha-smooth muscle actin in myofibroblasts was attenuated by Y-27632. Combining data from all groups identified ROCK-supported (Y-27632 inhibitable) expression of 10 transcripts, including ribonucleotide reductase M2, the cyclin B1-CDC2-CKS2 system, and four mitotic spindle-associated proteins. ROCK inhibition causes broad inhibition of DNA synthesis and mitosis and causes changes that are different between (bFGF-activated) fibroblasts and (TGF-beta 1-induced) myofibroblasts. Thus, Rho/ROCK signaling regulates both common and distinct downstream events in corneal stromal cells activated (differentiated) to fibroblast or myofibroblast phenotype.

Comparative Analysis of CNV Calling Algorithms: Literature Survey and a Case Study Using Bovine High-Density SNP Data.

PubMed

Xu, Lingyang; Hou, Yali; Bickhart, Derek M; Song, Jiuzhou; Liu, George E

2013-06-25

Copy number variations (CNVs) are gains and losses of genomic sequence between two individuals of a species when compared to a reference genome. The data from single nucleotide polymorphism (SNP) microarrays are now routinely used for genotyping, but they also can be utilized for copy number detection. Substantial progress has been made in array design and CNV calling algorithms and at least 10 comparison studies in humans have been published to assess them. In this review, we first survey the literature on existing microarray platforms and CNV calling algorithms. We then examine a number of CNV calling tools to evaluate their impacts using bovine high-density SNP data. Large incongruities in the results from different CNV calling tools highlight the need for standardizing array data collection, quality assessment and experimental validation. Only after careful experimental design and rigorous data filtering can the impacts of CNVs on both normal phenotypic variability and disease susceptibility be fully revealed.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

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

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis

PubMed Central

Peng, Zhi-yu; Zhou, Xin; Li, Linchuan; Yu, Xiangchun; Li, Hongjiang; Jiang, Zhiqiang; Cao, Guangyu; Bai, Mingyi; Wang, Xingchun; Jiang, Caifu; Lu, Haibin; Hou, Xianhui; Qu, Lijia; Wang, Zhiyong; Zuo, Jianru; Fu, Xiangdong; Su, Zhen; Li, Songgang; Guo, Hongwei

2009-01-01

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed. PMID:19015126

Arabidopsis Hormone Database: a comprehensive genetic and phenotypic information database for plant hormone research in Arabidopsis.

PubMed

Peng, Zhi-yu; Zhou, Xin; Li, Linchuan; Yu, Xiangchun; Li, Hongjiang; Jiang, Zhiqiang; Cao, Guangyu; Bai, Mingyi; Wang, Xingchun; Jiang, Caifu; Lu, Haibin; Hou, Xianhui; Qu, Lijia; Wang, Zhiyong; Zuo, Jianru; Fu, Xiangdong; Su, Zhen; Li, Songgang; Guo, Hongwei

2009-01-01

Plant hormones are small organic molecules that influence almost every aspect of plant growth and development. Genetic and molecular studies have revealed a large number of genes that are involved in responses to numerous plant hormones, including auxin, gibberellin, cytokinin, abscisic acid, ethylene, jasmonic acid, salicylic acid, and brassinosteroid. Here, we develop an Arabidopsis hormone database, which aims to provide a systematic and comprehensive view of genes participating in plant hormonal regulation, as well as morphological phenotypes controlled by plant hormones. Based on data from mutant studies, transgenic analysis and gene ontology (GO) annotation, we have identified a total of 1026 genes in the Arabidopsis genome that participate in plant hormone functions. Meanwhile, a phenotype ontology is developed to precisely describe myriad hormone-regulated morphological processes with standardized vocabularies. A web interface (http://ahd.cbi.pku.edu.cn) would allow users to quickly get access to information about these hormone-related genes, including sequences, functional category, mutant information, phenotypic description, microarray data and linked publications. Several applications of this database in studying plant hormonal regulation and hormone cross-talk will be presented and discussed.

Application of phenotypic microarrays to environmental microbiology

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

Borglin, sharon; Joyner, Dominique; DeAngelis, Kristen

2012-01-01

Environmental organisms are extremely diverse and only a small fraction has been successfully cultured in the laboratory. Culture in micro wells provides a method for rapid screening of a wide variety of growth conditions and commercially available plates contain a large number of substrates, nutrient sources, and inhibitors, which can provide an assessment of the phenotype of an organism. This review describes applications of phenotype arrays to anaerobic and thermophilic microorganisms, use of the plates in stress response studies, in development of culture media for newly discovered strains, and for assessment of phenotype of environmental communities. Also discussed are considerationsmore » and challenges in data interpretation and visualization, including data normalization, statistics, and curve fitting.« less

A rare de novo interstitial duplication of 15q15.3q21.2 in a boy with severe short stature, hypogonadism, global developmental delay and intellectual disability.

PubMed

Yuan, Haiming; Meng, Zhe; Zhang, Lina; Luo, Xiangyang; Liu, Liping; Chen, Mengfan; Li, Xinwei; Zhao, Weiwei; Liang, Liyang

2016-01-01

Interstitial duplications distal to 15q13 are very rare. Here, we reported a 14-year-old boy with severe short stature, delayed bone age, hypogonadism, global developmental delay and intellectual disability. His had distinctive facial features including macrocephaly, broad forehead, deep-set and widely spaced eyes, broad nose bridge, shallow philtrum and thick lips. A de novo 6.4 Mb interstitial duplication of 15q15.3q21.2 was detected by chromosomal microarray analysis. We compared our patient's clinical phenotypes with those of several individuals with overlapping duplications and several candidate genes responsible for the phenotypes were identified as well. The results suggest a novel contiguous gene duplication syndrome characterized with shared features including short stature, hypogonadism, global developmental delay and other congenital anomalies.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

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.

SRRM4 Expression and the Loss of REST Activity May Promote the Emergence of the Neuroendocrine Phenotype in Castration-Resistant Prostate Cancer.

PubMed

Zhang, Xiaotun; Coleman, Ilsa M; Brown, Lisha G; True, Lawrence D; Kollath, Lori; Lucas, Jared M; Lam, Hung-Ming; Dumpit, Ruth; Corey, Eva; Chéry, Lisly; Lakely, Bryce; Higano, Celestia S; Montgomery, Bruce; Roudier, Martine; Lange, Paul H; Nelson, Peter S; Vessella, Robert L; Morrissey, Colm

2015-10-15

The neuroendocrine phenotype is associated with the development of metastatic castration-resistant prostate cancer (CRPC). Our objective was to characterize the molecular features of the neuroendocrine phenotype in CRPC. Expression of chromogranin A (CHGA), synaptophysin (SYP), androgen receptor (AR), and prostate-specific antigen (PSA) was analyzed by IHC in 155 CRPC metastases from 50 patients and in 24 LuCaP prostate cancer patient-derived xenografts (PDX). Seventy-one of 155 metastases and the 24 LuCaP xenograft lines were analyzed by whole-genome microarrays. REST splicing was verified by PCR. Coexpression of CHGA and SYP in >30% of cells was observed in 22 of 155 metastases (9 patients); 11 of the 22 metastases were AR(+)/PSA(+) (6 patients), 11/22 were AR-/PSA- (4 patients), and 4/24 LuCaP PDXs were AR(-)/PSA(-). By IHC, of the 71 metastases analyzed by whole-genome microarrays, 5 metastases were CHGA(+)/SYP(+)/AR(-), and 5 were CHGA(+)/SYP(+)/AR(+). Only CHGA(+)/SYP(+) metastases had a neuroendocrine transcript signature. The neuronal transcriptional regulator SRRM4 transcript was associated with the neuroendocrine signature in CHGA(+)/SYP(+) metastases and all CHGA(+)/SYP(+) LuCaP xenografts. In addition, expression of SRRM4 in LuCaP neuroendocrine xenografts correlated with a splice variant of REST that lacks the transcriptional repressor domain. (i) Metastatic neuroendocrine status can be heterogeneous in the same patient, (ii) the CRPC neuroendocrine molecular phenotype can be defined by CHGA(+)/SYP(+) dual positivity, (iii) the neuroendocrine phenotype is not necessarily associated with the loss of AR activity, and (iv) the splicing of REST by SRRM4 could promote the neuroendocrine phenotype in CRPC. ©2015 American Association for Cancer Research.

Transcriptome profiling of a Saccharomyces cerevisiae mutant with a constitutively activated Ras/cAMP pathway.

PubMed

Jones, D L; Petty, J; Hoyle, D C; Hayes, A; Ragni, E; Popolo, L; Oliver, S G; Stateva, L I

2003-12-16

Often changes in gene expression levels have been considered significant only when above/below some arbitrarily chosen threshold. We investigated the effect of applying a purely statistical approach to microarray analysis and demonstrated that small changes in gene expression have biological significance. Whole genome microarray analysis of a pde2Delta mutant, constructed in the Saccharomyces cerevisiae reference strain FY23, revealed altered expression of approximately 11% of protein encoding genes. The mutant, characterized by constitutive activation of the Ras/cAMP pathway, has increased sensitivity to stress, reduced ability to assimilate nonfermentable carbon sources, and some cell wall integrity defects. Applying the Munich Information Centre for Protein Sequences (MIPS) functional categories revealed increased expression of genes related to ribosome biogenesis and downregulation of genes in the cell rescue, defense, cell death and aging category, suggesting a decreased response to stress conditions. A reduced level of gene expression in the unfolded protein response pathway (UPR) was observed. Cell wall genes whose expression was affected by this mutation were also identified. Several of the cAMP-responsive orphan genes, upon further investigation, revealed cell wall functions; others had previously unidentified phenotypes assigned to them. This investigation provides a statistical global transcriptome analysis of the cellular response to constitutive activation of the Ras/cAMP pathway.

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

PubMed

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

2014-01-01

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

Prognostic significance of MYC, BCL2, and BCL6 rearrangements in patients with diffuse large B-cell lymphoma treated with cyclophosphamide, doxorubicin, vincristine, and prednisone plus rituximab.

PubMed

Akyurek, Nalan; Uner, Aysegul; Benekli, Mustafa; Barista, Ibrahim

2012-09-01

Diffuse large B-cell lymphomas (DLBCLs) are a biologically heterogeneous group in which various gene alterations have been reported. The aim of this study was to investigate the frequency and prognostic impact of BCL2, BCL6, and MYC rearrangements in cyclophosphamide, doxorubicin, vincristine, and prednisone plus rituximab (R-CHOP)-treated DLBCL cases. Tissue microarrays were constructed from 239 cases of DLBCL, and the expressions of CD10, BCL6, MUM1/IRF4, and BCL2 were evaluated by immunohistochemistry. MYC, BCL2, and BCL6 rearrangements were investigated by interphase fluorescence in situ hybridization on tissue microarrays. Survival analysis was constructed from 145 R-CHOP-treated patients. MYC, BCL2, and BCL6 rearrangements were detected in 14 (6%), 36 (15%), and 69 (29%) of 239 DLBCL patients. Double or triple rearrangements were detected in 7 (3%) of 239 DLBCL cases. Of these, 4 had BCL2 and MYC, 2 had BCL6 and MYC, and 1 had BCL2, BCL6, and MYC rearrangements. The prognosis of these cases was extremely poor, with a median survival of 9 months. MYC rearrangement was associated with significantly worse overall survival (P = .01), especially for the cases with GC phenotype (P = .009). BCL6 rearrangement also predicted significantly shorter overall survival (P = .04), especially for the non-GC phenotype (P = .03). BCL2 rearrangement had no prognostic impact on outcome. International Prognostic Index (P = .004) and MYC rearrangement (P = .009) were independent poor prognostic factors. Analysis of MYC gene rearrangement along with BCL2 and BCL6 is critical in identifying high-risk patients with poor prognosis. Copyright © 2011 American Cancer Society.

4p16.3 microdeletions and microduplications detected by chromosomal microarray analysis: New insights into mechanisms and critical regions.

PubMed

Bi, Weimin; Cheung, Sau-Wai; Breman, Amy M; Bacino, Carlos A

2016-10-01

Deletions in the 4p16.3 region cause Wolf-Hirschhorn syndrome, a well known contiguous microdeletion syndrome with the critical region for common phenotype mapped in WHSCR2. Recently, duplications in 4p16.3 were reported in three patients with developmental delay and dysmorphic features. Through chromosomal microarray analysis, we identified 156 patients with a deletion (n = 109) or duplication (n = 47) in 4p16.3 out of approximately 60,000 patients analyzed by Baylor Miraca Genetics Laboratories. Seventy-five of the postnatally detected deletions encompassed the entire critical region, 32 (43%) of which were associated with other chromosome rearrangements, including six patients (8%) that had a duplication adjacent to the terminal deletion. Our data indicate that Wolf-Hirschhorn syndrome deletions with an adjacent duplication occur at a higher frequency than previously appreciated. Pure deletions (n = 14) or duplications (n = 15) without other copy number changes distal to or inside the WHSCR2 were identified for mapping of critical regions. Our data suggest that deletion of the segment from 0.6 to 0.9 Mb from the terminus of 4p causes a seizure phenotype and duplications of a region distal to the previously defined smallest region of overlap for 4p16.3 microduplication syndrome are associated with neurodevelopmental problems. We detected seven Wolf-Hirschhorn syndrome deletions and one 4p16.3 duplication prenatally; all of the seven are either >8 Mb in size and/or associated with large duplications. In conclusion, our study provides deeper insight into the molecular mechanisms, the critical regions and effective prenatal diagnosis for 4p16.3 deletions/ duplications. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Gene profiling of cathepsin K deficiency in atherogenesis: profibrotic but lipogenic.

PubMed

Lutgens, S P M; Kisters, N; Lutgens, E; van Haaften, R I M; Evelo, C T A; de Winther, M P J; Saftig, P; Daemen, M J A P; Heeneman, S; Cleutjens, K B J M

2006-11-01

Recently, we showed that cathepsin K deficiency reduces atherosclerotic plaque progression, induces plaque fibrosis, but aggravates macrophage foam cell formation in the ApoE -/- mouse. To obtain more insight into the molecular mechanisms by which cathepsin K disruption evokes the observed phenotypic changes, we used microarray analysis for gene expression profiling of aortic arches of CatK -/-/ApoE -/- and ApoE -/- mice on a mouse oligo microarray. Out of 20 280 reporters, 444 were significantly differentially expressed (p-value of < 0.05, fold change of > or = 1.4 or < or = - 1.4, and intensity value of > 2.5 times background in at least one channel). Ingenuity Pathway Analysis and GenMAPP revealed upregulation of genes involved in lipid uptake, trafficking, and intracellular storage, including caveolin - 1, - 2, - 3 and CD36, and profibrotic genes involved in transforming growth factor beta (TGFbeta) signalling, including TGFbeta2, latent TGFbeta binding protein-1 (LTBP1), and secreted protein, acidic and rich in cysteine (SPARC), in CatK -/-/ApoE -/- mice. Differential gene expression was confirmed at the mRNA and protein levels. In vitro modified low density lipoprotein (LDL) uptake assays, using bone marrow derived macrophages preincubated with caveolae and scavenger receptor inhibitors, confirmed the importance of caveolins and CD36 in increasing modified LDL uptake in the absence of cathepsin K. In conclusion, we suggest that cathepsin K deficiency alters plaque phenotype not only by decreasing proteolytic activity, but also by stimulating TGFbeta signalling. Besides this profibrotic effect, cathepsin K deficiency has a lipogenic effect owing to increased lipid uptake mediated by CD36 and caveolins. Copyright 2006 Pathological Society of Great Britain and Ireland.

Molecular genetic anatomy of inter- and intraserotype variation in the human bacterial pathogen group A Streptococcus.

PubMed

Beres, Stephen B; Richter, Ellen W; Nagiec, Michal J; Sumby, Paul; Porcella, Stephen F; DeLeo, Frank R; Musser, James M

2006-05-02

In recent years we have studied the relationship between strain genotypes and patient phenotypes in group A Streptococcus (GAS), a model human bacterial pathogen that causes extensive morbidity and mortality worldwide. We have concentrated our efforts on serotype M3 organisms because these strains are common causes of pharyngeal and invasive infections, produce unusually severe invasive infections, and can exhibit epidemic behavior. Our studies have been hindered by the lack of genome-scale phylogenies of multiple GAS strains and whole-genome sequences of multiple serotype M3 strains recovered from individuals with defined clinical phenotypes. To remove some of these impediments, we sequenced to closure the genome of four additional GAS strains and conducted comparative genomic resequencing of 12 contemporary serotype M3 strains representing distinct genotypes and phenotypes. Serotype M3 strains are a single phylogenetic lineage. Strains from asymptomatic throat carriers were significantly less virulent for mice than sterile-site isolates and evolved to a less virulent phenotype by multiple genetic pathways. Strain persistence or extinction between epidemics was strongly associated with presence or absence, respectively, of the prophage encoding streptococcal pyrogenic exotoxin A. A serotype M3 clone significantly underrepresented among necrotizing fasciitis cases has a unique frameshift mutation that truncates MtsR, a transcriptional regulator controlling expression of genes encoding iron-acquisition proteins. Expression microarray analysis of this clone confirmed significant alteration in expression of genes encoding iron metabolism proteins. Our analysis provided unprecedented detail about the molecular anatomy of bacterial strain genotype-patient phenotype relationships.

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

Sensitivity analysis of gene ranking methods in phenotype prediction.

PubMed

deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan L; Sonis, Stephen T

2016-12-01

It has become clear that noise generated during the assay and analytical processes has the ability to disrupt accurate interpretation of genomic studies. Not only does such noise impact the scientific validity and costs of studies, but when assessed in the context of clinically translatable indications such as phenotype prediction, it can lead to inaccurate conclusions that could ultimately impact patients. We applied a sequence of ranking methods to damp noise associated with microarray outputs, and then tested the utility of the approach in three disease indications using publically available datasets. This study was performed in three phases. We first theoretically analyzed the effect of noise in phenotype prediction problems showing that it can be expressed as a modeling error that partially falsifies the pathways. Secondly, via synthetic modeling, we performed the sensitivity analysis for the main gene ranking methods to different types of noise. Finally, we studied the predictive accuracy of the gene lists provided by these ranking methods in synthetic data and in three different datasets related to cancer, rare and neurodegenerative diseases to better understand the translational aspects of our findings. In the case of synthetic modeling, we showed that Fisher's Ratio (FR) was the most robust gene ranking method in terms of precision for all the types of noise at different levels. Significance Analysis of Microarrays (SAM) provided slightly lower performance and the rest of the methods (fold change, entropy and maximum percentile distance) were much less precise and accurate. The predictive accuracy of the smallest set of high discriminatory probes was similar for all the methods in the case of Gaussian and Log-Gaussian noise. In the case of class assignment noise, the predictive accuracy of SAM and FR is higher. Finally, for real datasets (Chronic Lymphocytic Leukemia, Inclusion Body Myositis and Amyotrophic Lateral Sclerosis) we found that FR and SAM provided the highest predictive accuracies with the smallest number of genes. Biological pathways were found with an expanded list of genes whose discriminatory power has been established via FR. We have shown that noise in expression data and class assignment partially falsifies the sets of discriminatory probes in phenotype prediction problems. FR and SAM better exploit the principle of parsimony and are able to find subsets with less number of high discriminatory genes. The predictive accuracy and the precision are two different metrics to select the important genes, since in the presence of noise the most predictive genes do not completely coincide with those that are related to the phenotype. Based on the synthetic results, FR and SAM are recommended to unravel the biological pathways that are involved in the disease development. Copyright © 2016 Elsevier Inc. All rights reserved.

Separate enrichment analysis of pathways for up- and downregulated genes.

PubMed

Hong, Guini; Zhang, Wenjing; Li, Hongdong; Shen, Xiaopei; Guo, Zheng

2014-03-06

Two strategies are often adopted for enrichment analysis of pathways: the analysis of all differentially expressed (DE) genes together or the analysis of up- and downregulated genes separately. However, few studies have examined the rationales of these enrichment analysis strategies. Using both microarray and RNA-seq data, we show that gene pairs with functional links in pathways tended to have positively correlated expression levels, which could result in an imbalance between the up- and downregulated genes in particular pathways. We then show that the imbalance could greatly reduce the statistical power for finding disease-associated pathways through the analysis of all-DE genes. Further, using gene expression profiles from five types of tumours, we illustrate that the separate analysis of up- and downregulated genes could identify more pathways that are really pertinent to phenotypic difference. In conclusion, analysing up- and downregulated genes separately is more powerful than analysing all of the DE genes together.

Epigenetic transgenerational inheritance of somatic transcriptomes and epigenetic control regions

PubMed Central

2012-01-01

Background Environmentally induced epigenetic transgenerational inheritance of adult onset disease involves a variety of phenotypic changes, suggesting a general alteration in genome activity. Results Investigation of different tissue transcriptomes in male and female F3 generation vinclozolin versus control lineage rats demonstrated all tissues examined had transgenerational transcriptomes. The microarrays from 11 different tissues were compared with a gene bionetwork analysis. Although each tissue transgenerational transcriptome was unique, common cellular pathways and processes were identified between the tissues. A cluster analysis identified gene modules with coordinated gene expression and each had unique gene networks regulating tissue-specific gene expression and function. A large number of statistically significant over-represented clusters of genes were identified in the genome for both males and females. These gene clusters ranged from 2-5 megabases in size, and a number of them corresponded to the epimutations previously identified in sperm that transmit the epigenetic transgenerational inheritance of disease phenotypes. Conclusions Combined observations demonstrate that all tissues derived from the epigenetically altered germ line develop transgenerational transcriptomes unique to the tissue, but common epigenetic control regions in the genome may coordinately regulate these tissue-specific transcriptomes. This systems biology approach provides insight into the molecular mechanisms involved in the epigenetic transgenerational inheritance of a variety of adult onset disease phenotypes. PMID:23034163

Pure mechanistic analysis of additive neuroprotective effects between baicalin and jasminoidin in ischemic stroke mice.

PubMed

Wang, Peng-Qian; Liu, Qiong; Xu, Wen-Juan; Yu, Ya-Nan; Zhang, Ying-Ying; Li, Bing; Liu, Jun; Wang, Zhong

2018-06-01

Both baicalin (BA) and jasminoidin (JA) are active ingredients in Chinese herb medicine Scutellaria baicalensis and Fructus gardeniae, respectively. They have been shown to exert additive neuroprotective action in ischemic stroke models. In this study we used transcriptome analysis to explore the pure therapeutic mechanisms of BA, JA and their combination (BJ) contributing to phenotype variation and reversal of pathological processes. Mice with middle cerebral artery obstruction were treated with BA, JA, their combination (BJ), or concha margaritifera (CM). Cerebral infarct volume was examined to determine the effect of these compounds on phenotype. Using the hippocampus microarray and ingenuity pathway analysis (IPA) software, we exacted the differentially expressed genes, networks, pathways, and functions in positive-phenotype groups (BA, JA and BJ) by comparing with the negative-phenotype group (CM). In the BA, JA, and BJ groups, a total of 7, 4, and 11 specific target molecules, 1, 1, and 4 networks, 51, 59, and 18 canonical pathways and 70, 53, and 64 biological functions, respectively, were identified. Pure therapeutic mechanisms of BA and JA were mainly overlapped in specific target molecules, functions and pathways, which were related to the nervous system, inflammation and immune response. The specific mechanisms of BA and JA were associated with apoptosis and cancer-related signaling and endocrine and hormone regulation, respectively. In the BJ group, novel target profiles distinct from mono-therapies were revealed, including 11 specific target molecules, 10 functions, and 10 pathways, the majority of which were related to a virus-mediated immune response. The pure additive effects between BA and JA were based on enhanced action in virus-mediated immune response. This pure mechanistic analysis may provide a clearer outline of the target profiles of multi-target compounds and combination therapies.

Histological Stratification of Thick and Thin Plaque Psoriasis Explores Molecular Phenotypes with Clinical Implications

PubMed Central

Kim, Dong Joo; Brodmerkel, Carrie; Correa da Rosa, Joel; Krueger, James G.; Suárez-Fariñas, Mayte

2015-01-01

Psoriasis, which presents as red, scaly patches on the body, is a common, autoimmune skin disease that affects 2 to 3 percent of the world population. To leverage recent molecular findings into the personalized treatment of psoriasis, we need a strategy that integrates clinical stratification with molecular phenotyping. In this study, we sought to stratify psoriasis patients by histological measurements of epidermal thickness, and to compare their molecular characterizations by gene expression, serum cytokines, and response to biologics. We obtained histological measures of epidermal thickness in a cohort of 609 psoriasis patients, and identified a mixture of two subpopulations—thick and thin plaque psoriasis—from which they were derived. This stratification was verified in a subcohort of 65 patients from a previously published study with significant differences in inflammatory cell infiltrates in the psoriatic skin. Thick and thin plaque psoriasis shared 84.8% of the meta-analysis-derived psoriasis transcriptome, but a stronger dysregulation of the meta-analysis-derived psoriasis transcriptome was seen in thick plaque psoriasis on microarray. RT-PCR revealed that gene expression in thick and thin plaque psoriasis was different not only within psoriatic lesional skin but also in peripheral non-lesional skin. Additionally, differences in circulating cytokines and their changes in response to biologic treatments were found between the two subgroups. All together, we were able to integrate histological stratification with molecular phenotyping as a way of exploring clinical phenotypes with different expression levels of the psoriasis transcriptome and circulating cytokines. PMID:26176783

Functional Analysis With a Barcoder Yeast Gene Overexpression System

PubMed Central

Douglas, Alison C.; Smith, Andrew M.; Sharifpoor, Sara; Yan, Zhun; Durbic, Tanja; Heisler, Lawrence E.; Lee, Anna Y.; Ryan, Owen; Göttert, Hendrikje; Surendra, Anu; van Dyk, Dewald; Giaever, Guri; Boone, Charles; Nislow, Corey; Andrews, Brenda J.

2012-01-01

Systematic analysis of gene overexpression phenotypes provides an insight into gene function, enzyme targets, and biological pathways. Here, we describe a novel functional genomics platform that enables a highly parallel and systematic assessment of overexpression phenotypes in pooled cultures. First, we constructed a genome-level collection of ~5100 yeast barcoder strains, each of which carries a unique barcode, enabling pooled fitness assays with a barcode microarray or sequencing readout. Second, we constructed a yeast open reading frame (ORF) galactose-induced overexpression array by generating a genome-wide set of yeast transformants, each of which carries an individual plasmid-born and sequence-verified ORF derived from the Saccharomyces cerevisiae full-length EXpression-ready (FLEX) collection. We combined these collections genetically using synthetic genetic array methodology, generating ~5100 strains, each of which is barcoded and overexpresses a specific ORF, a set we termed “barFLEX.” Additional synthetic genetic array allows the barFLEX collection to be moved into different genetic backgrounds. As a proof-of-principle, we describe the properties of the barFLEX overexpression collection and its application in synthetic dosage lethality studies under different environmental conditions. PMID:23050238

Using expression genetics to study the neurobiology of ethanol and alcoholism.

PubMed

Farris, Sean P; Wolen, Aaron R; Miles, Michael F

2010-01-01

Recent simultaneous progress in human and animal model genetics and the advent of microarray whole genome expression profiling have produced prodigious data sets on genetic loci, potential candidate genes, and differential gene expression related to alcoholism and ethanol behaviors. Validated target genes or gene networks functioning in alcoholism are still of meager proportions. Genetical genomics, which combines genetic analysis of both traditional phenotypes and whole genome expression data, offers a potential methodology for characterizing brain gene networks functioning in alcoholism. This chapter will describe concepts, approaches, and recent findings in the field of genetical genomics as it applies to alcohol research. Copyright 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

2010-10-21

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

The phenotypic spectrum of ARHGEF9 includes intellectual disability, focal epilepsy and febrile seizures.

PubMed

Klein, Karl Martin; Pendziwiat, Manuela; Eilam, Anda; Gilad, Ronit; Blatt, Ilan; Rosenow, Felix; Kanaan, Moien; Helbig, Ingo; Afawi, Zaid

2017-07-01

Mutations or structural genomic alterations of the X-chromosomal gene ARHGEF9 have been described in male and female patients with intellectual disability. Hyperekplexia and epilepsy were observed to a variable degree, but incompletely described. Here, we expand the phenotypic spectrum of ARHGEF9 by describing a large Ethiopian-Jewish family with epilepsy and intellectual disability. The four affected male siblings, their unaffected parents and two unaffected female siblings were recruited and phenotyped. Parametric linkage analysis was performed using SNP microarrays. Variants from exome sequencing in two affected individuals were confirmed by Sanger sequencing. All affected male siblings had febrile seizures from age 2-3 years and intellectual disability. Three developed afebrile seizures between age 7-17 years. Three showed focal seizure semiology. None had hyperekplexia. A novel ARHGEF9 variant (c.967G>A, p.G323R, NM_015185.2) was hemizygous in all affected male siblings and heterozygous in the mother. This family reveals that the phenotypic spectrum of ARHGEF9 is broader than commonly assumed and includes febrile seizures and focal epilepsy with intellectual disability in the absence of hyperekplexia or other clinically distinguishing features. Our findings suggest that pathogenic variants in ARHGEF9 may be more common than previously assumed in patients with intellectual disability and mild epilepsy.

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,…

Loss of the Mechanotransducer Zyxin Promotes a Synthetic Phenotype of Vascular Smooth Muscle Cells

PubMed Central

Ghosh, Subhajit; Kollar, Branislav; Nahar, Taslima; Suresh Babu, Sahana; Wojtowicz, Agnieszka; Sticht, Carsten; Gretz, Norbert; Wagner, Andreas H; Korff, Thomas; Hecker, Markus

2015-01-01

Background Exposure of vascular smooth muscle cells (VSMCs) to excessive cyclic stretch such as in hypertension causes a shift in their phenotype. The focal adhesion protein zyxin can transduce such biomechanical stimuli to the nucleus of both endothelial cells and VSMCs, albeit with different thresholds and kinetics. However, there is no distinct vascular phenotype in young zyxin-deficient mice, possibly due to functional redundancy among other gene products belonging to the zyxin family. Analyzing zyxin function in VSMCs at the cellular level might thus offer a better mechanistic insight. We aimed to characterize zyxin-dependent changes in gene expression in VSMCs exposed to biomechanical stretch and define the functional role of zyxin in controlling the resultant VSMC phenotype. Methods and Results DNA microarray analysis was used to identify genes and pathways that were zyxin regulated in static and stretched human umbilical artery–derived and mouse aortic VSMCs. Zyxin-null VSMCs showed a remarkable shift to a growth-promoting, less apoptotic, promigratory and poorly contractile phenotype with ≈90% of the stretch-responsive genes being zyxin dependent. Interestingly, zyxin-null cells already seemed primed for such a synthetic phenotype, with mechanical stretch further accentuating it. This could be accounted for by higher RhoA activity and myocardin-related transcription factor-A mainly localized to the nucleus of zyxin-null VSMCs, and a condensed and localized accumulation of F-actin upon stretch. Conclusions At the cellular level, zyxin is a key regulator of stretch-induced gene expression. Loss of zyxin drives VSMCs toward a synthetic phenotype, a process further consolidated by exaggerated stretch. PMID:26071033

A curated collection of tissue microarray images and clinical outcome data of prostate cancer patients

PubMed Central

Zhong, Qing; Guo, Tiannan; Rechsteiner, Markus; Rüschoff, Jan H.; Rupp, Niels; Fankhauser, Christian; Saba, Karim; Mortezavi, Ashkan; Poyet, Cédric; Hermanns, Thomas; Zhu, Yi; Moch, Holger; Aebersold, Ruedi; Wild, Peter J.

2017-01-01

Microscopy image data of human cancers provide detailed phenotypes of spatially and morphologically intact tissues at single-cell resolution, thus complementing large-scale molecular analyses, e.g., next generation sequencing or proteomic profiling. Here we describe a high-resolution tissue microarray (TMA) image dataset from a cohort of 71 prostate tissue samples, which was hybridized with bright-field dual colour chromogenic and silver in situ hybridization probes for the tumour suppressor gene PTEN. These tissue samples were digitized and supplemented with expert annotations, clinical information, statistical models of PTEN genetic status, and computer source codes. For validation, we constructed an additional TMA dataset for 424 prostate tissues, hybridized with FISH probes for PTEN, and performed survival analysis on a subset of 339 radical prostatectomy specimens with overall, disease-specific and recurrence-free survival (maximum 167 months). For application, we further produced 6,036 image patches derived from two whole slides. Our curated collection of prostate cancer data sets provides reuse potential for both biomedical and computational studies. PMID:28291248

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

PubMed Central

Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

2008-01-01

Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

PubMed

Zhang, Zhe; Fenstermacher, David

2005-01-01

Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

Stanniocalcin 2 is an estrogen-responsive gene coexpressed with the estrogen receptor in human breast cancer.

PubMed

Bouras, Toula; Southey, Melissa C; Chang, Andy C; Reddel, Roger R; Willhite, Dorian; Glynne, Richard; Henderson, Michael A; Armes, Jane E; Venter, Deon J

2002-03-01

Differences in gene expression are likely to explain the phenotypic variation between hormone-responsive and hormone-unresponsive breast cancers. In this study, DNA microarray analysis of approximately 10,000 known genes and 25,000 expressed sequence tag clusters was performed to identify genes induced by estrogen and repressed by the pure antiestrogen ICI 182 780 in vitro that correlated with estrogen receptor (ER) expression in primary breast carcinomas in vivo. Stanniocalcin (STC) 2 was identified as one of the genes that fulfilled these criteria. DNA microarray hybridization showed a 3-fold induction of STC2 mRNA expression in MCF-7 cells in < or = 3 h of estrogen exposure and a 3-fold repression in the presence of antiestrogen (one-way ANOVA, P < 0.0005). In 13 ER-positive and 12 ER-negative breast carcinomas, the microarray-derived mRNA levels observed for STC2 correlated with tumor ER mRNA (Pearson's correlation, r = 0.85; P < 0.0001) and ER protein status (Spearman's rank correlation, r = 0.73; P < 0.0001). The expression profile of STC2 was further confirmed by in situ hybridization and immunohistochemistry on a larger cohort of 236 unselected breast carcinomas using tissue microarrays. STC2 mRNA and protein expression were found to be associated with tumor ER status (Fisher's exact test, P < 0.005). The related gene, STC1, was also examined and shown to be associated with ER status in breast carcinomas (Fisher's exact test, P < 0.05). This study demonstrates the feasibility of using global gene expression data derived from an in vitro model to pinpoint novel estrogen-responsive genes of potential clinical relevance.

Impact of genotyping errors on statistical power of association tests in genomic analyses: A case study

PubMed Central

Hou, Lin; Sun, Ning; Mane, Shrikant; Sayward, Fred; Rajeevan, Nallakkandi; Cheung, Kei-Hoi; Cho, Kelly; Pyarajan, Saiju; Aslan, Mihaela; Miller, Perry; Harvey, Philip D.; Gaziano, J. Michael; Concato, John; Zhao, Hongyu

2017-01-01

A key step in genomic studies is to assess high throughput measurements across millions of markers for each participant’s DNA, either using microarrays or sequencing techniques. Accurate genotype calling is essential for downstream statistical analysis of genotype-phenotype associations, and next generation sequencing (NGS) has recently become a more common approach in genomic studies. How the accuracy of variant calling in NGS-based studies affects downstream association analysis has not, however, been studied using empirical data in which both microarrays and NGS were available. In this article, we investigate the impact of variant calling errors on the statistical power to identify associations between single nucleotides and disease, and on associations between multiple rare variants and disease. Both differential and nondifferential genotyping errors are considered. Our results show that the power of burden tests for rare variants is strongly influenced by the specificity in variant calling, but is rather robust with regard to sensitivity. By using the variant calling accuracies estimated from a substudy of a Cooperative Studies Program project conducted by the Department of Veterans Affairs, we show that the power of association tests is mostly retained with commonly adopted variant calling pipelines. An R package, GWAS.PC, is provided to accommodate power analysis that takes account of genotyping errors (http://zhaocenter.org/software/). PMID:28019059

Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes.

PubMed

Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

2015-09-30

Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

"Something Extra on Chromosome 5": Parents' Understanding of Positive Prenatal Chromosomal Microarray Analysis (CMA) Results.

PubMed

Walser, Sarah A; Werner-Lin, Allison; Russell, Amita; Wapner, Ronald J; Bernhardt, Barbara A

2016-10-01

This study aims to explore how couples' understanding of the nature and consequences of positive prenatal chromosomal microarray analysis (CMA) results impacts decision-making and concern about pregnancy. We interviewed 28 women and 12 male partners after receiving positive results and analyzed the transcripts to assess their understanding and level of concern about the expected clinical implications of results. Participant descriptions were compared to the original laboratory interpretation. When diagnosed prenatally, couples' understanding of the nature and consequences of copy number variants (CNVs) impacts decision-making and concern. Findings suggest women, but less so partners, generally understand the nature and clinical implications of prenatal CMA results. Couples feel reassured, perhaps sometimes falsely so, when a CNV is inherited from a "normal" parent and experience considerable uncertainty when a CNV is de novo, frequently precipitating a search for additional information and guidance. Five factors influenced participants' concern including: the pattern of inheritance, type of possible phenotypic involvement, perceived manageability of outcomes, availability and strength of evidence about outcomes associated with the CNV, and provider messages about continuing the pregnancy. A good understanding of results is vital as couples decide whether or not to continue with their pregnancy and seek additional information to assist in pregnancy decision-making.

Molecular essence and endocrine responsiveness of estrogen receptor-negative, progesterone receptor-positive, and HER2-negative breast cancer.

PubMed

Yu, Ke-Da; Jiang, Yi-Zhou; Hao, Shuang; Shao, Zhi-Ming

2015-10-05

The clinical significance of progesterone receptor (PgR) expression in estrogen receptor-negative (ER-) breast cancer is controversial. Herein, we systemically investigate the clinicopathologic features, molecular essence, and endocrine responsiveness of ER-/PgR+/HER2- phenotype. Four study cohorts were included. The first and second cohorts were from the Surveillance, Epidemiology, and End Results database (n = 67,932) and Fudan University Shanghai Cancer Center (n = 2,338), respectively, for clinicopathologic and survival analysis. The third and fourth cohorts were from two independent publicly available microarray datasets including 837 operable cases and 483 cases undergoing neoadjuvant chemotherapy, respectively, for clinicopathologic and gene-expression analysis. Characterized genes defining subgroups within the ER-/PgR+/HER2- phenotype were determined and further validated. Clinicopathologic features and survival outcomes of the ER-/PgR+ phenotype fell in between the ER+/PgR+ and ER-/PgR- phenotypes, but were more similar to ER-/PgR-. Among the ER-/PgR+ phenotype, 30% (95% confidence interval [CI] 17-42%, pooled by a fixed-effects method) were luminal-like and 59% (95% CI 45-72%, pooled by a fixed-effects method) were basal-like. We further refined the characterized genes for subtypes within the ER-/PgR+ phenotype and developed an immunohistochemistry-based method that could determine the molecular essence of ER-/PgR+ using three markers, TFF1, CK5, and EGFR. Either PAM50-defined or immunohistochemistry-defined basal-like ER-/PgR+ cases have a lower endocrine therapy sensitivity score compared with luminal-like ER-/PgR+ cases (P <0.0001 by Mann-Whitney test for each study set and P <0.0001 for pooled standardized mean difference in meta-analysis). Immunohistochemistry-defined basal-like ER-/PgR+ cases might not benefit from adjuvant endocrine therapy (log-rank P = 0.61 for sufficient versus insufficient endocrine therapy). The majority of ER-/PgR+/HER2- phenotype breast cancers are basal-like and associated with a lower endocrine therapy sensitivity score. Additional studies are needed to validate these findings.

Short stature, unusual face, delta phalanx, and abnormal vertebrae and ribs in a girl born to half-siblings.

PubMed

Pogue, Robert; Marques, Felipe A; Kopacek, Cristiane; Rosa, Rosana C M; Dorfman, Luiza E; Mazzeu, Juliana F; Flores, José A M; Zen, Paulo R G; Rosa, Rafael F M

2017-05-01

Delta phalanx is a rare abnormality typically associated with additional features. We describe a patient with a phenotype resembling Catel-Manzke syndrome, but with delta phalanx and abnormal vertebrae and ribs. The patient was the only child of half siblings born with a marked prenatal growth deficiency. At 10 years of age, she had a short stature, long face, long and tubular nose with small alae nasi, high palate, short and broad thorax, and short index fingers with radial deviation. There were hyperpigmentations following Blaschko's lines. Radiology showed a proximal delta phalanx in the index finger of hands, abnormal vertebrae, and fused and small ribs. GTG-Banding karyotype and microarray analysis yielded normal results. Exome sequencing identified 25 genes that harbored homozygous variants, but none of these is assumed to be a good candidate to explain (part of) the phenotype. The here described patient may have a new condition, possibly following an autosomal recessive pattern of inheritance, although due to the high degree of consanguinity a compound etiology of the phenotype by variants in various genes may be present as well. © 2017 Wiley Periodicals, Inc.

A crucial role of ROCK for alleviation of senescence-associated phenotype.

PubMed

Park, Joon Tae; Kang, Hyun Tae; Park, Chi Hyun; Lee, Young-Sam; Cho, Kyung A; Park, Sang Chul

2018-06-01

In our previous study, we uncovered a novel mechanism in which amelioration of Hutchinson-Gilford progeria syndrome (HGPS) phenotype is mediated by mitochondrial functional recovery upon rho-associated protein kinase (ROCK) inhibition. However, it remains elusive whether this mechanism is also applied to the amelioration of normal aging cells. In this study, we used Y-27632 and fasudil as effective ROCK inhibitors, and examined their role in senescence. We found that ROCK inhibition induced the functional recovery of the mitochondria as well as the metabolic reprogramming, which are two salient features that are altered in normal aging cells. Moreover, microarray analysis revealed that the up-regulated pathway upon ROCK inhibition is enriched for chromatin remodeling genes, which may play an important role in the alleviation of senescence-associated cell cycle arrest. Indeed, ROCK inhibition induced cellular proliferation, concomitant with the amelioration of senescent phenotype. Furthermore, the restorative effect by ROCK inhibition was observed in vivo as evidenced by the facilitated cutaneous wound healing. Taken together, our data indicate that ROCK inhibition might be utilized to ameliorate normal aging process and to treat age-related disease. Copyright © 2018 Elsevier Inc. All rights reserved.

[Generation and phenotype analysis of zebrafish mutations of obesity-related genes lepr and mc4r].

PubMed

Fei, Fei; Sun, Shao-Yang; Yao, Yu-Xiao; Wang, Xu

2017-02-25

Obesity has become a severe public health problem across the world, and seriously affects the health and life quality of human beings. Here we generated lepr and mc4r mutant zebrafish via the CRISPR/Cas9 technique, and performed morphological and functional characterizations of those mutants. We observed that there was no significant phenotypic difference between homozygous mutants and wild-type controls before 2.5 months post-fertilization (mpf). However, the adult lepr -/- and mc4r -/- individuals displayed increased food intake, heavier weight, and higher body fat percentage, the characteristics of obesity phenotypes. Blood glucose test showed that overfeeding induced significantly impaired glucose tolerance in adult lepr -/- and mc4r -/- zebrafish. Furthermore, we analyzed 76 energy metabolism-related transcripts in lepr -/- and mc4r -/- zebrafish livers by using real-time RT-PCR, and compared the results with the published microarray data of Lep ob/ob mouse livers, and found that the changes in the expression of insulin/IGF signaling (IIS) pathway genes in lepr -/- zebrafish and Lep ob/ob mouse were positively correlated, suggesting that the IIS pathway maintains functional conservation between zebrafish and mammals during the evolution of the obesity-regulating molecule network.

A de novo 2q35-q36.1 deletion incorporating IHH in a Chinese boy (47,XYY) with syndactyly, type III Waardenburg syndrome, and congenital heart disease.

PubMed

Wang, D; Ren, G F; Zhang, H Z; Yi, C Y; Peng, Z J

2016-12-02

Reports of terminal and interstitial deletions of the long arm of chromosome 2 are rare in the literature. Here, we present a case report concerning a Chinese boy with a 47,XYY karyotype and a de novo deletion comprising approximately 5 Mb between 2q35 and q36.1, along with syndactyly, type III Waardenburg syndrome, and congenital heart disease. High-resolution chromosome analysis to detect copy number variations was carried out using an Affymetrix microarray platform, and the genes affected by the patient's deletion, including IHH, were determined. However, no copy number changes were observed in his healthy parents. The present case exhibited novel syndactyly features, broadening the spectrum of clinical findings observed in individuals with 2q interstitial deletions. Our data, together with previous observations, suggest that IHH haploinsufficiency is the principal pathogenic factor in the syndactyly phenotype in this study, and that different types of variations at the IHH locus may cause divergent disease phenotypes. This is the first report of the involvement of IHH haploinsufficiency in syndactyly phenotype.

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

PubMed

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

2013-01-01

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

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

Chromosomal microarray testing identifies a 4p terminal region associated with seizures in Wolf–Hirschhorn syndrome

PubMed Central

South, Sarah T; Lortz, Amanda; Hensel, Charles H; Sdano, Mallory R; Vanzo, Rena J; Martin, Megan M; Peiffer, Andreas; Lambert, Christophe G; Calhoun, Amy; Carey, John C; Battaglia, Agatino

2016-01-01

Background Wolf–Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. Methods Using chromosomal microarray analysis, we finely mapped the breakpoints of copy number variants (CNVs) in 48 individuals with WHS. Seizure phenotype data were collected through parent-reported answers to a comprehensive questionnaire and supplemented with available medical records. Results We observed a significant correlation between the presence of an interstitial 4p deletion and lack of a seizure phenotype (Fisher's exact test p=3.59e-6). In our cohort, there were five individuals with interstitial deletions with a distal breakpoint at least 751 kbp proximal to the 4p terminus. Four of these individuals have never had an observable seizure, and the fifth individual had a single febrile seizure at the age of 1.5 years. All other individuals in our cohort whose deletions encompass the terminal 751 kbp region report having seizures typical of WHS. Additional examples from the literature corroborate these observations and further refine the candidate seizure susceptibility region to a region 197 kbp in size, starting 368 kbp from the terminus of chromosome 4. Conclusions We identify a small terminal region of chromosome 4p that represents a seizure susceptibility region. Deletion of this region in the context of WHS is sufficient for seizure occurrence. PMID:26747863

A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder

PubMed Central

Prasad, Aparna; Merico, Daniele; Thiruvahindrapuram, Bhooma; Wei, John; Lionel, Anath C.; Sato, Daisuke; Rickaby, Jessica; Lu, Chao; Szatmari, Peter; Roberts, Wendy; Fernandez, Bridget A.; Marshall, Christian R.; Hatchwell, Eli; Eis, Peggy S.; Scherer, Stephen W.

2012-01-01

The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection. PMID:23275889

High Frequency of Copy-Neutral Loss of Heterozygosity in Patients with Myelofibrosis.

PubMed

Rego de Paula Junior, Milton; Nonino, Alexandre; Minuncio Nascimento, Juliana; Bonadio, Raphael S; Pic-Taylor, Aline; de Oliveira, Silviene F; Wellerson Pereira, Rinaldo; do Couto Mascarenhas, Cintia; Forte Mazzeu, Juliana

2018-01-01

Myelofibrosis is the rarest and most severe type of Philadelphia-negative classical myeloproliferative neoplasms. Although mutually exclusive driver mutations in JAK2, MPL, or CALR that activate JAK-STAT pathway have been related to the pathogenesis of the disease, chromosome abnormalities have also been associated with the phenotype and prognosis of the disease. Here, we report the use of a chromosomal microarray platform consisting of both oligo and SNP probes to improve the detection of chromosome abnormalities in patients with myelofibrosis. Sixteen patients with myelofibrosis were tested, and the results were compared to karyotype analysis. Driver mutations in JAK2, MPL, or CALR were investigated by PCR and MLPA. Conventional cytogenetics revealed chromosome abnormalities in 3 out of 16 cases (18.7%), while chromosomal microarray analysis detected copy-number variations (CNV) or copy-neutral loss of heterozygosity (CN-LOH) alterations in 11 out of 16 (68.7%) patients. These included 43 CN-LOH, 14 deletions, 1 trisomy, and 1 duplication. Ten patients showed multiple chromosomal abnormalities, varying from 2 to 13 CNVs or CN-LOHs. Mutational status for JAK2, CALR, and MPL by MLPA revealed a total of 3/16 (18.7%) patients positive for the JAK2 V617F mutation, 9 with CALR deletion or insertion and 1 positive for MPL mutation. Considering that most of the CNVs identified were smaller than the karyotype resolution and the high frequency of CN-LOHs in our study, we propose that chromosomal microarray platforms that combine oligos and SNP should be used as a first-tier genetic test in patients with myelofibrosis. © 2018 S. Karger AG, Basel.

Mobile Interspersed Repeats Are Major Structural Variants in the Human Genome

PubMed Central

Huang, Cheng Ran Lisa; Schneider, Anna M.; Lu, Yunqi; Niranjan, Tejasvi; Shen, Peilin; Robinson, Matoya A.; Steranka, Jared P.; Valle, David; Civin, Curt I.; Wang, Tao; Wheelan, Sarah J.; Ji, Hongkai; Boeke, Jef D.; Burns, Kathleen H.

2010-01-01

Summary Characterizing structural variants in the human genome is of great importance, but a genome wide analysis to detect interspersed repeats has not been done. Thus, the degree to which mobile DNAs contribute to genetic diversity, heritable disease, and oncogenesis remains speculative. We perform transposon insertion profiling by microarray (TIP-chip) to map human L1(Ta) retrotransposons (LINE-1 s) genome-wide. This identified numerous novel human L1(Ta) insertional polymorphisms with highly variant allelic frequencies. We also explored TIP-chip's usefulness to identify candidate alleles associated with different phenotypes in clinical cohorts. Our data suggest that the occurrence of new insertions is twice as high as previously estimated, and that these repeats are under-recognized as sources of human genomic and phenotypic diversity. We have just begun to probe the universe of human L1(Ta) polymorphisms, and as TIP-chip is applied to other insertions such as Alu SINEs, it will expand the catalog of genomic variants even further. PMID:20602999

PROSPECT improves cis-acting regulatory element prediction by integrating expression profile data with consensus pattern searches

PubMed Central

Fujibuchi, Wataru; Anderson, John S. J.; Landsman, David

2001-01-01

Consensus pattern and matrix-based searches designed to predict cis-acting transcriptional regulatory sequences have historically been subject to large numbers of false positives. We sought to decrease false positives by incorporating expression profile data into a consensus pattern-based search method. We have systematically analyzed the expression phenotypes of over 6000 yeast genes, across 121 expression profile experiments, and correlated them with the distribution of 14 known regulatory elements over sequences upstream of the genes. Our method is based on a metric we term probabilistic element assessment (PEA), which is a ranking of potential sites based on sequence similarity in the upstream regions of genes with similar expression phenotypes. For eight of the 14 known elements that we examined, our method had a much higher selectivity than a naïve consensus pattern search. Based on our analysis, we have developed a web-based tool called PROSPECT, which allows consensus pattern-based searching of gene clusters obtained from microarray data. PMID:11574681

Chimerism for 20q11.2 microdeletion of GDF5 explains discordant phenotypes in monochorionic-diamniotic twins.

PubMed

Meredith, Matthew M; Crabb, Beau; Vargas, Marcelo; Hirsch, Betsy A

2017-12-01

Microdeletions of 20q11.2 are rare but have been associated with characteristic clinical findings. A 1.6 Mb minimal critical region has been identified that includes three OMIM genes: GDF5, EPB41L1, and SAMHD. Here we describe a male monozygotic, monochorionic-diamniotic twin pair with discordant phenotypes, one with multiple findings that overlap with those reported in 20q11.2 deletions, and the other unaffected. Microarray analysis revealed mosaicism for a 363 Kb deletion encompassing GDF5 in the peripheral blood of both twins, which was confirmed by FISH. Subsequent FISH on buccal cells identified the deletion only in the affected twin. The blood FISH findings were interpreted as representing chimerism resulting from anastomosis and the blood exchange between the twins in utero. The implications of this finding are discussed, as is the contribution of GDF5 to the associated clinical findings of 20q11.2 deletions. © 2017 Wiley Periodicals, Inc.

Axenfeld-Rieger syndrome: further clinical and array delineation of four unrelated patients with a 4q25 microdeletion.

PubMed

Titheradge, Hannah; Togneri, Fiona; McMullan, Dominic; Brueton, Louise; Lim, Derek; Williams, Denise

2014-07-01

Axenfeld-Rieger syndrome (ARS) is an autosomal dominant disorder with variable expressivity. It is characterized by dysgenesis of the anterior segment of the eye together with dental, cardiac, and umbilical anomalies. There is a high incidence of secondary high tension glaucoma. It is a genetically heterogeneous condition due to deletion or mutations of FOXC1 (6p25) or PITX2 (4q25). We report on four unrelated patients with overlapping microdeletions encompassing PITX2 at 4q25. We compare the genotypes and phenotypes of these newly described ARS patients and discuss the involvement of contiguous genes. Patients 1, 2, and 3 had mild learning difficulties, not typically seen in patients with ARS. We implicate the adjacent neuronally expressed genes; NEUROG2, UGT8, NDST3, and PRSS12 as potentially causal. Our findings support the use of microarray analysis in ARS patients for full prognostic information in infants presenting with ARS-like phenotypes. © 2014 Wiley Periodicals, Inc.

Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images.

PubMed

Spagnolo, Daniel M; Al-Kofahi, Yousef; Zhu, Peihong; Lezon, Timothy R; Gough, Albert; Stern, Andrew M; Lee, Adrian V; Ginty, Fiona; Sarachan, Brion; Taylor, D Lansing; Chennubhotla, S Chakra

2017-11-01

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. Cancer Res; 77(21); e71-74. ©2017 AACR . ©2017 American Association for Cancer Research.

Identifying transcription factor functions and targets by phenotypic activation

PubMed Central

Chua, Gordon; Morris, Quaid D.; Sopko, Richelle; Robinson, Mark D.; Ryan, Owen; Chan, Esther T.; Frey, Brendan J.; Andrews, Brenda J.; Boone, Charles; Hughes, Timothy R.

2006-01-01

Mapping transcriptional regulatory networks is difficult because many transcription factors (TFs) are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual TFs that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast TFs that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, indicating that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5′-TCACGCAA as a binding sequence for Hms1p, a TF that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of TF activities and mapping targets that could be adapted to any organism with transgenic technology. PMID:16880382

Microarray technology for major chemical contaminants analysis in food: current status and prospects.

PubMed

Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

2012-01-01

Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

A de novo 1q22q23.1 Interstitial Microdeletion in a Girl with Intellectual Disability and Multiple Congenital Anomalies Including Congenital Heart Defect.

PubMed

Aleksiūnienė, Beata; Preiksaitiene, Egle; Morkūnienė, Aušra; Ambrozaitytė, Laima; Utkus, Algirdas

2018-01-01

Many studies have shown that molecular karyotyping is an effective diagnostic tool in individuals with developmental delay/intellectual disability. We report on a de novo interstitial 1q22q23.1 microdeletion, 1.6 Mb in size, detected in a patient with short stature, microcephaly, hypoplastic corpus callosum, cleft palate, minor facial anomalies, congenital heart defect, camptodactyly of the 4-5th fingers, and intellectual disability. Chromosomal microarray analysis revealed a 1.6-Mb deletion in the 1q22q23.1 region, arr[GRCh37] 1q22q23.1(155630752_157193893)×1. Real-time PCR analysis confirmed its de novo origin. The deleted region encompasses 50 protein-coding genes, including the morbid genes APOA1BP, ARHGEF2, LAMTOR2, LMNA, NTRK1, PRCC, RIT1, SEMA4A, and YY1AP1. Although the unique phenotype observed in our patient can arise from the haploinsufficiency of the dosage-sensitive LMNA gene, the dosage imbalance of other genes implicated in the rearrangement could also contribute to the phenotype. Further studies are required for the delineation of the phenotype associated with this rare chromosomal alteration and elucidation of the critical genes for manifestation of the specific clinical features. © 2018 S. Karger AG, Basel.

Design of Biomedical Robots for Phenotype Prediction Problems

PubMed Central

deAndrés-Galiana, Enrique J.; Sonis, Stephen T.

2016-01-01

Abstract Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem. PMID:27347715

Design of Biomedical Robots for Phenotype Prediction Problems.

PubMed

deAndrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Sonis, Stephen T

2016-08-01

Genomics has been used with varying degrees of success in the context of drug discovery and in defining mechanisms of action for diseases like cancer and neurodegenerative and rare diseases in the quest for orphan drugs. To improve its utility, accuracy, and cost-effectiveness optimization of analytical methods, especially those that translate to clinically relevant outcomes, is critical. Here we define a novel tool for genomic analysis termed a biomedical robot in order to improve phenotype prediction, identifying disease pathogenesis and significantly defining therapeutic targets. Biomedical robot analytics differ from historical methods in that they are based on melding feature selection methods and ensemble learning techniques. The biomedical robot mathematically exploits the structure of the uncertainty space of any classification problem conceived as an ill-posed optimization problem. Given a classifier, there exist different equivalent small-scale genetic signatures that provide similar predictive accuracies. We perform the sensitivity analysis to noise of the biomedical robot concept using synthetic microarrays perturbed by different kinds of noises in expression and class assignment. Finally, we show the application of this concept to the analysis of different diseases, inferring the pathways and the correlation networks. The final aim of a biomedical robot is to improve knowledge discovery and provide decision systems to optimize diagnosis, treatment, and prognosis. This analysis shows that the biomedical robots are robust against different kinds of noises and particularly to a wrong class assignment of the samples. Assessing the uncertainty that is inherent to any phenotype prediction problem is the right way to address this kind of problem.

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.

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…

Phenotypic plasticity and targeting of Siglec-F(high) CD11c(low) eosinophils to the airway in a murine model of asthma.

PubMed

Abdala Valencia, H; Loffredo, L F; Misharin, A V; Berdnikovs, S

2016-02-01

Eosinophil recruitment in asthma is a multistep process, involving both trans-endothelial migration to the lung interstitium and trans-epithelial migration into the airways. While the trans-endothelial step is well studied, trans-epithelial recruitment is less understood. To contrast eosinophil recruitment between these two compartments, we employed a murine kinetics model of asthma. Eosinophils were phenotyped by multicolor flow cytometry in digested lung tissue and bronchoalveolar lavage (BAL) simultaneously, 6 h after each ovalbumin (OVA) challenge. There was an early expansion of tissue eosinophils after OVA challenge followed by eosinophil buildup in both compartments and a shift in phenotype over the course of the asthma model. Gradual transition from a Siglec-F(med) CD11c(-) to a Siglec-F(high) CD11c(low) phenotype in lung tissue was associated with eosinophil recruitment to the airways, as all BAL eosinophils were of the latter phenotype. Secondary microarray analysis of tissue-activated eosinophils demonstrated upregulation of specific integrin and chemokine receptor signature suggesting interaction with the mucosa. Using adhesion assays, we demonstrated that integrin CD11c mediated adhesion of eosinophils to fibrinogen, a significant component of epithelial barrier repair and remodeling. To the best of our knowledge, this is the only report to date dissecting compartmentalization of eosinophil recruitment as it unfolds during allergic inflammation. By capturing the kinetics of eosinophil phenotypic change in both tissue and BAL using flow cytometry and sorting, we were able to demonstrate a previously undocumented association between phenotypic shift of tissue-recruited eosinophils and their trans-epithelial movement, which implicates the existence of a specific mechanism targeting these cells to mucosal airways. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Chromosomal microarray in clinical diagnosis: a study of 337 patients with congenital anomalies and developmental delays or intellectual disability.

PubMed

Sansović, Ivona; Ivankov, Ana-Maria; Bobinec, Adriana; Kero, Mijana; Barišić, Ingeborg

2017-06-14

To determine the diagnostic yield and criteria that could help to classify and interpret the copy number variations (CNVs) detected by chromosomal microarray (CMA) technique in patients with congenital and developmental abnormalities including dysmorphia, developmental delay (DD) or intellectual disability (ID), autism spectrum disorders (ASD) and congenital anomalies (CA). CMA analysis was performed in 337 patients with DD/ID with or without dysmorphism, ASD, and/or CA. In 30 of 337 patients, chromosomal imbalances had previously been detected by classical cytogenetic and molecular cytogenetic methods. In 73 of 337 patients, clinically relevant variants were detected and better characterized. Most of them were >1 Mb. Variants of unknown clinical significance (VOUS) were discovered in 35 patients. The most common VOUS size category was <300 kb (40.5%). Deletions and de novo imbalances were more frequent in pathogenic CNV than in VOUS category. CMA had a high diagnostic yield of 43/307, excluding patients previously detected by other methods. CMA was valuable in establishing the diagnosis in a high proportion of patients. Criteria for classification and interpretation of CNVs include CNV size and type, mode of inheritance, and genotype-phenotype correlation. Agilent ISCA v2 Human Genome 8x60 K oligonucleotide microarray format proved to be reasonable resolution for clinical use, particularly in the regions that are recommended by the International Standard Cytogenomic Array (ISCA) Consortium and associated with well-established syndromes.

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.

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

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

Integrating Microarray Data and GRNs.

PubMed

Koumakis, L; Potamias, G; Tsiknakis, M; Zervakis, M; Moustakis, V

2016-01-01

With the completion of the Human Genome Project and the emergence of high-throughput technologies, a vast amount of molecular and biological data are being produced. Two of the most important and significant data sources come from microarray gene-expression experiments and respective databanks (e,g., Gene Expression Omnibus-GEO (http://www.ncbi.nlm.nih.gov/geo)), and from molecular pathways and Gene Regulatory Networks (GRNs) stored and curated in public (e.g., Kyoto Encyclopedia of Genes and Genomes-KEGG (http://www.genome.jp/kegg/pathway.html), Reactome (http://www.reactome.org/ReactomeGWT/entrypoint.html)) as well as in commercial repositories (e.g., Ingenuity IPA (http://www.ingenuity.com/products/ipa)). The association of these two sources aims to give new insight in disease understanding and reveal new molecular targets in the treatment of specific phenotypes.Three major research lines and respective efforts that try to utilize and combine data from both of these sources could be identified, namely: (1) de novo reconstruction of GRNs, (2) identification of Gene-signatures, and (3) identification of differentially expressed GRN functional paths (i.e., sub-GRN paths that distinguish between different phenotypes). In this chapter, we give an overview of the existing methods that support the different types of gene-expression and GRN integration with a focus on methodologies that aim to identify phenotype-discriminant GRNs or subnetworks, and we also present our methodology.

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Framework for reanalysis of publicly available Affymetrix® GeneChip® data sets based on functional regions of interest.

PubMed

Saka, Ernur; Harrison, Benjamin J; West, Kirk; Petruska, Jeffrey C; Rouchka, Eric C

2017-12-06

Since the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One main drawback to microarray data analysis involves the selection of probes to represent a specific transcript of interest, particularly in light of the fact that transcript-specific knowledge (notably alternative splicing) is dynamic in nature. We therefore developed a framework for reannotating and reassigning probe groups for Affymetrix® GeneChip® technology based on functional regions of interest. This framework addresses three issues of Affymetrix® GeneChip® data analyses: removing nonspecific probes, updating probe target mapping based on the latest genome knowledge and grouping probes into gene, transcript and region-based (UTR, individual exon, CDS) probe sets. Updated gene and transcript probe sets provide more specific analysis results based on current genomic and transcriptomic knowledge. The framework selects unique probes, aligns them to gene annotations and generates a custom Chip Description File (CDF). The analysis reveals only 87% of the Affymetrix® GeneChip® HG-U133 Plus 2 probes uniquely align to the current hg38 human assembly without mismatches. We also tested new mappings on the publicly available data series using rat and human data from GSE48611 and GSE72551 obtained from GEO, and illustrate that functional grouping allows for the subtle detection of regions of interest likely to have phenotypical consequences. Through reanalysis of the publicly available data series GSE48611 and GSE72551, we profiled the contribution of UTR and CDS regions to the gene expression levels globally. The comparison between region and gene based results indicated that the detected expressed genes by gene-based and region-based CDFs show high consistency and regions based results allows us to detection of changes in transcript formation.

Teaching bioinformatics and neuroinformatics by using free web-based tools.

PubMed

Grisham, William; Schottler, Natalie A; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson

2010-01-01

This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with anatomy (Mouse Brain Library), quantitative trait locus analysis (WebQTL from GeneNetwork), bioinformatics and gene expression analyses (University of California, Santa Cruz Genome Browser, National Center for Biotechnology Information's Entrez Gene, and the Allen Brain Atlas), and information resources (PubMed). Instructors can use these various websites in concert to teach genetics from the phenotypic level to the molecular level, aspects of neuroanatomy and histology, statistics, quantitative trait locus analysis, and molecular biology (including in situ hybridization and microarray analysis), and to introduce bioinformatic resources. Students use these resources to discover 1) the region(s) of chromosome(s) influencing the phenotypic trait, 2) a list of candidate genes-narrowed by expression data, 3) the in situ pattern of a given gene in the region of interest, 4) the nucleotide sequence of the candidate gene, and 5) articles describing the gene. Teaching materials such as a detailed student/instructor's manual, PowerPoints, sample exams, and links to free Web resources can be found at http://mdcune.psych.ucla.edu/modules/bioinformatics.

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice[S

PubMed Central

Leduc, Magalie S.; Hageman, Rachael S.; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2011-01-01

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a “toolbox” of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits. PMID:21622629

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

Molecular Diagnostic Yield of Chromosomal Microarray Analysis and Whole-Exome Sequencing in Children With Autism Spectrum Disorder.

PubMed

Tammimies, Kristiina; Marshall, Christian R; Walker, Susan; Kaur, Gaganjot; Thiruvahindrapuram, Bhooma; Lionel, Anath C; Yuen, Ryan K C; Uddin, Mohammed; Roberts, Wendy; Weksberg, Rosanna; Woodbury-Smith, Marc; Zwaigenbaum, Lonnie; Anagnostou, Evdokia; Wang, Zhuozhi; Wei, John; Howe, Jennifer L; Gazzellone, Matthew J; Lau, Lynette; Sung, Wilson W L; Whitten, Kathy; Vardy, Cathy; Crosbie, Victoria; Tsang, Brian; D'Abate, Lia; Tong, Winnie W L; Luscombe, Sandra; Doyle, Tyna; Carter, Melissa T; Szatmari, Peter; Stuckless, Susan; Merico, Daniele; Stavropoulos, Dimitri J; Scherer, Stephen W; Fernandez, Bridget A

2015-09-01

The use of genome-wide tests to provide molecular diagnosis for individuals with autism spectrum disorder (ASD) requires more study. To perform chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) in a heterogeneous group of children with ASD to determine the molecular diagnostic yield of these tests in a sample typical of a developmental pediatric clinic. The sample consisted of 258 consecutively ascertained unrelated children with ASD who underwent detailed assessments to define morphology scores based on the presence of major congenital abnormalities and minor physical anomalies. The children were recruited between 2008 and 2013 in Newfoundland and Labrador, Canada. The probands were stratified into 3 groups of increasing morphological severity: essential, equivocal, and complex (scores of 0-3, 4-5, and ≥6). All probands underwent CMA, with WES performed for 95 proband-parent trios. The overall molecular diagnostic yield for CMA and WES in a population-based ASD sample stratified in 3 phenotypic groups. Of 258 probands, 24 (9.3%, 95%CI, 6.1%-13.5%) received a molecular diagnosis from CMA and 8 of 95 (8.4%, 95%CI, 3.7%-15.9%) from WES. The yields were statistically different between the morphological groups. Among the children who underwent both CMA and WES testing, the estimated proportion with an identifiable genetic etiology was 15.8% (95%CI, 9.1%-24.7%; 15/95 children). This included 2 children who received molecular diagnoses from both tests. The combined yield was significantly higher in the complex group when compared with the essential group (pairwise comparison, P = .002). [table: see text]. Among a heterogeneous sample of children with ASD, the molecular diagnostic yields of CMA and WES were comparable, and the combined molecular diagnostic yield was higher in children with more complex morphological phenotypes in comparison with the children in the essential category. If replicated in additional populations, these findings may inform appropriate selection of molecular diagnostic testing for children affected by ASD.

WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

Identification of novel target genes involved in Indian Fanconi anemia patients using microarray.

PubMed

Shyamsunder, Pavithra; Ganesh, Kripa S; Vidyasekar, Prasanna; Mohan, Sheila; Verma, Rama Shanker

2013-12-01

Fanconi anemia (FA) is a genetic disorder characterized by progressive bone marrow failure and a predisposition to cancers. Mutations have been documented in 15 FA genes that participate in the FA-BRCA DNA repair pathway, a fundamental pathway in the development of the disease and the presentation of its characteristic symptoms. Certain symptoms such as oxygen sensitivity, hematological abnormalities and impaired immunity suggest that FA proteins could participate in or independently control other pathways as well. In this study, we identified 9 DNA repair genes that were down regulated in a genome wide analysis of 6 Indian Fanconi anemia patients. Functional clustering of a total of 233 dysregulated genes identified key biological processes that included regulation of transcription, DNA repair, cell cycle and chromosomal organization. Microarray data revealed the down regulation of ATXN3, ARID4A and ETS-1, which were validated by RTPCR in a subsequent sample set of 9 Indian FA patients. Here we report for the first time a gene expression profile of Fanconi anemia patients from the Indian population and a pool of genes that might aid in the acquisition and progression of the FA phenotype. © 2013 Elsevier B.V. All rights reserved.

Mitochondrial dysfunction, oxidative stress and apoptosis revealed by proteomic and transcriptomic analyses of the striata in two mouse models of Parkinson’s disease

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

Chin, Mark H.; Qian, Weijun; Wang, Haixing

2008-02-10

The molecular mechanisms underlying the changes in the nigrostriatal pathway in Parkinson disease (PD) are not completely understood. Here we use mass spectrometry and microarrays to study the proteomic and transcriptomic changes in the striatum of two mouse models of PD, induced by the distinct neurotoxins 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and methamphetamine (METH). Proteomic analyses resulted in the identification and relative quantification of 912 proteins with two or more unique peptides and 85 proteins with significant abundance changes following neurotoxin treatment. Similarly, microarray analyses revealed 181 genes with significant changes in mRNA following neurotoxin treatment. The combined protein and gene list providesmore » a clearer picture of the potential mechanisms underlying neurodegeneration observed in PD. Functional analysis of this combined list revealed a number of significant categories, including mitochondrial dysfunction, oxidative stress response and apoptosis. Additionally, codon usage and miRNAs may play an important role in translational control in the striatum. These results constitute one of the largest datasets integrating protein and transcript changes for these neurotoxin models with many similar endpoint phenotypes but distinct mechanisms.« less

Transcriptome profiling in engrailed-2 mutant mice reveals common molecular pathways associated with autism spectrum disorders.

PubMed

Sgadò, Paola; Provenzano, Giovanni; Dassi, Erik; Adami, Valentina; Zunino, Giulia; Genovesi, Sacha; Casarosa, Simona; Bozzi, Yuri

2013-12-19

Transcriptome analysis has been used in autism spectrum disorder (ASD) to unravel common pathogenic pathways based on the assumption that distinct rare genetic variants or epigenetic modifications affect common biological pathways. To unravel recurrent ASD-related neuropathological mechanisms, we took advantage of the En2-/- mouse model and performed transcriptome profiling on cerebellar and hippocampal adult tissues. Cerebellar and hippocampal tissue samples from three En2-/- and wild type (WT) littermate mice were assessed for differential gene expression using microarray hybridization followed by RankProd analysis. To identify functional categories overrepresented in the differentially expressed genes, we used integrated gene-network analysis, gene ontology enrichment and mouse phenotype ontology analysis. Furthermore, we performed direct enrichment analysis of ASD-associated genes from the SFARI repository in our differentially expressed genes. Given the limited number of animals used in the study, we used permissive criteria and identified 842 differentially expressed genes in En2-/- cerebellum and 862 in the En2-/- hippocampus. Our functional analysis revealed that the molecular signature of En2-/- cerebellum and hippocampus shares convergent pathological pathways with ASD, including abnormal synaptic transmission, altered developmental processes and increased immune response. Furthermore, when directly compared to the repository of the SFARI database, our differentially expressed genes in the hippocampus showed enrichment of ASD-associated genes significantly higher than previously reported. qPCR was performed for representative genes to confirm relative transcript levels compared to those detected in microarrays. Despite the limited number of animals used in the study, our bioinformatic analysis indicates the En2-/- mouse is a valuable tool for investigating molecular alterations related to ASD.

FDA Escherichia coli Identification (FDA-ECID) Microarray: a Pangenome Molecular Toolbox for Serotyping, Virulence Profiling, Molecular Epidemiology, and Phylogeny

PubMed Central

Patel, Isha R.; Gangiredla, Jayanthi; Lacher, David W.; Mammel, Mark K.; Jackson, Scott A.; Lampel, Keith A.

2016-01-01

ABSTRACT Most Escherichia coli strains are nonpathogenic. However, for clinical diagnosis and food safety analysis, current identification methods for pathogenic E. coli either are time-consuming and/or provide limited information. Here, we utilized a custom DNA microarray with informative genetic features extracted from 368 sequence sets for rapid and high-throughput pathogen identification. The FDA Escherichia coli Identification (FDA-ECID) platform contains three sets of molecularly informative features that together stratify strain identification and relatedness. First, 53 known flagellin alleles, 103 alleles of wzx and wzy, and 5 alleles of wzm provide molecular serotyping utility. Second, 41,932 probe sets representing the pan-genome of E. coli provide strain-level gene content information. Third, approximately 125,000 single nucleotide polymorphisms (SNPs) of available whole-genome sequences (WGS) were distilled to 9,984 SNPs capable of recapitulating the E. coli phylogeny. We analyzed 103 diverse E. coli strains with available WGS data, including those associated with past foodborne illnesses, to determine robustness and accuracy. The array was able to accurately identify the molecular O and H serotypes, potentially correcting serological failures and providing better resolution for H-nontypeable/nonmotile phenotypes. In addition, molecular risk assessment was possible with key virulence marker identifications. Epidemiologically, each strain had a unique comparative genomic fingerprint that was extended to an additional 507 food and clinical isolates. Finally, a 99.7% phylogenetic concordance was established between microarray analysis and WGS using SNP-level data for advanced genome typing. Our study demonstrates FDA-ECID as a powerful tool for epidemiology and molecular risk assessment with the capacity to profile the global landscape and diversity of E. coli. IMPORTANCE This study describes a robust, state-of-the-art platform developed from available whole-genome sequences of E. coli and Shigella spp. by distilling useful signatures for epidemiology and molecular risk assessment into one assay. The FDA-ECID microarray contains features that enable comprehensive molecular serotyping and virulence profiling along with genome-scale genotyping and SNP analysis. Hence, it is a molecular toolbox that stratifies strain identification and pathogenic potential in the contexts of epidemiology and phylogeny. We applied this tool to strains from food, environmental, and clinical sources, resulting in significantly greater phylogenetic and strain-specific resolution than previously reported for available typing methods. PMID:27037122

Phenotypic and genotypic characteristics of Staphylococcus aureus isolates from zoo and wild animals.

PubMed

Feßler, Andrea T; Thomas, Patricia; Mühldorfer, Kristin; Grobbel, Mirjam; Brombach, Julian; Eichhorn, Inga; Monecke, Stefan; Ehricht, Ralf; Schwarz, Stefan

2018-05-01

Antimicrobial resistance of Staphylococcus aureus is a major problem in human and veterinary medicine. The aim of this study was to characterise S. aureus isolates from wild and zoo animals mainly associated with bacterial infections. In total, 23 S. aureus isolates, including nine from wild animals and 14 from zoo animals, were obtained during routine diagnostics. All isolates were subjected to multilocus sequence typing (MLST), spa typing, macrorestriction analysis with subsequent SmaI pulsed-field gelelectrophoresis (PFGE), antimicrobial susceptibility testing and S. aureus-specific DNA-microarray analysis. Resistant isolates were also tested for their respective resistance genes by PCR. Isolates from zoo animals and wildlife showed a high diversity of MLST types, spa types and PFGE patterns. Nineteen different spa types were identified, including three novel types and 16 main macrorestriction patterns. Only few isolates were resistant to members of four classes of antimicrobial agents and harboured the respective resistance genes (β-lactams [blaZ, mecA, mecC], tetracyclines [tet(K), tet(L)] and chloramphenicol [cat pC221 ]) or mutations (fluoroquinolones). The DNA microarray analysis identified one isolate from a zoo animal harbouring the toxic shock syndrome toxin gene tst1. Moreover, several enterotoxin genes were detected in five S. aureus isolates. All isolates were negative for Panton-Valentine leukocidin (PVL) genes, but the animal-associated leukocidin genes lukM/lukF-P83 were found in three isolates from two animals. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel orthotopic mouse model of head and neck cancer and lymph node metastasis

PubMed Central

Masood, R; Hochstim, C; Cervenka, B; Zu, S; Baniwal, S K; Patel, V; Kobielak, A; Sinha, U K

2013-01-01

Prognosis of head and neck squamous cell carcinoma (HNSCC) is largely determined by the extent of lymph node (LN) metastasis at diagnosis, and this appears to be controlled by cancer cell genetics. To examine the role of these genes in LN metastasis, we created a human-in-mouse orthotopic model of HNSCC and performed comparative microarray analysis of gene expression between populations of HNSCC cell lines derived before and after serial transplantation and in vivo metastasis in mice. Microarray analysis comparing the USC-HN3-GFP, USC-HN3-GFP-G1 and USC-HN3-GFP-G2 cell lines identified overexpression of genes implicated in epithelial-to- mesenchymal transition and the formation of cancer stem cells, including CAV-1, TLR-4 (Toll-like receptor 4), MMP-7 (matrix metalloproteinase 7), ALDH1A3, OCT-4 and TRIM-29. Ingenuity Pathway Analysis confirmed upregulation of respective gene signaling pathways in the USC-HN1-GFP-G2 cell line. Patient HNSCC samples from advanced stages overexpressed ALDH1A3, CAV-1 and MMP-7. Our results show that CAV-1, TLR-4, MMP-7, ALDH1A3, OCT-4 and TRIM-29 have increased expression in HNSCC cells selected for an enhanced metastatic phenotype and suggest that these genes may have an important role in the metastatic potential of HNSCC cells. Inhibition of these genes may therefore have prognostic and therapeutic utility in HNSCC. PMID:24018643

Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma.

PubMed

Yan, Xiting; Chu, Jen-Hwa; Gomez, Jose; Koenigs, Maria; Holm, Carole; He, Xiaoxuan; Perez, Mario F; Zhao, Hongyu; Mane, Shrikant; Martinez, Fernando D; Ober, Carole; Nicolae, Dan L; Barnes, Kathleen C; London, Stephanie J; Gilliland, Frank; Weiss, Scott T; Raby, Benjamin A; Cohn, Lauren; Chupp, Geoffrey L

2015-05-15

The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease. Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes. Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 × 10(-6)) and hospitalization (P = 0.01), respectively. There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma.

Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma

PubMed Central

Yan, Xiting; Chu, Jen-Hwa; Gomez, Jose; Koenigs, Maria; Holm, Carole; He, Xiaoxuan; Perez, Mario F.; Zhao, Hongyu; Mane, Shrikant; Martinez, Fernando D.; Ober, Carole; Nicolae, Dan L.; Barnes, Kathleen C.; London, Stephanie J.; Gilliland, Frank; Weiss, Scott T.; Raby, Benjamin A.; Cohn, Lauren

2015-01-01

Rationale: The airway transcriptome includes genes that contribute to the pathophysiologic heterogeneity seen in individuals with asthma. Objectives: We analyzed sputum gene expression for transcriptomic endotypes of asthma (TEA), gene signatures that discriminate phenotypes of disease. Methods: Gene expression in the sputum and blood of patients with asthma was measured using Affymetrix microarrays. Unsupervised clustering analysis based on pathways from the Kyoto Encyclopedia of Genes and Genomes was used to identify TEA clusters. Logistic regression analysis of matched blood samples defined an expression profile in the circulation to determine the TEA cluster assignment in a cohort of children with asthma to replicate clinical phenotypes. Measurements and Main Results: Three TEA clusters were identified. TEA cluster 1 had the most subjects with a history of intubation (P = 0.05), a lower prebronchodilator FEV1 (P = 0.006), a higher bronchodilator response (P = 0.03), and higher exhaled nitric oxide levels (P = 0.04) compared with the other TEA clusters. TEA cluster 2, the smallest cluster, had the most subjects that were hospitalized for asthma (P = 0.04). TEA cluster 3, the largest cluster, had normal lung function, low exhaled nitric oxide levels, and lower inhaled steroid requirements. Evaluation of TEA clusters in children confirmed that TEA clusters 1 and 2 are associated with a history of intubation (P = 5.58 × 10−6) and hospitalization (P = 0.01), respectively. Conclusions: There are common patterns of gene expression in the sputum and blood of children and adults that are associated with near-fatal, severe, and milder asthma. PMID:25763605

Polymer microarray technology for stem cell engineering

PubMed Central

Coyle, Robert; Jia, Jia; Mei, Ying

2015-01-01

Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. During the past decade, significant progress has been made in developing soluble factors (e.g., small molecules and growth factors) to direct stem cells into a desired phenotype. However, the current lack of suitable synthetic materials to regulate stem cell activity has limited the realization of the enormous potential of stem cells. This can be attributed to a large number of materials properties (e.g., chemical structures and physical properties of materials) that can affect stem cell fate. This makes it challenging to design biomaterials to direct stem cell behavior. To address this, polymer microarray technology has been developed to rapidly identify materials for a variety of stem cell applications. In this article, we summarize recent developments in polymer array technology and their applications in stem cell engineering. Statement of significance Stem cells hold remarkable promise for applications in tissue engineering and disease modeling. In the last decade, significant progress has been made in developing chemically defined media to direct stem cells into a desired phenotype. However, the current lack of the suitable synthetic materials to regulate stem cell activities has been limiting the realization of the potential of stem cells. This can be attributed to the number of variables in material properties (e.g., chemical structures and physical properties) that can affect stem cells. Polymer microarray technology has shown to be a powerful tool to rapidly identify materials for a variety of stem cell applications. Here we summarize recent developments in polymer array technology and their applications in stem cell engineering. PMID:26497624

An enhanced Petri-net model to predict synergistic effects of pairwise drug combinations from gene microarray data.

PubMed

Jin, Guangxu; Zhao, Hong; Zhou, Xiaobo; Wong, Stephen T C

2011-07-01

Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations from the molecular response profiles, i.e. drug-treated microarray data. We addressed the downstream signaling network of the targets for the two individual drugs used in the pairwise combinations and applied EPN to the identified targeted signaling network. In EPN, drugs and signaling molecules are assigned to different types of places, while drug doses and molecular expressions are denoted by color tokens. The changes of molecular expressions caused by treatments of drugs are simulated by two actions of EPN: firing and blasting. Firing is to transit the drug and molecule tokens from one node or place to another, and blasting is to reduce the number of molecule tokens by drug tokens in a molecule node. The goal of EPN is to mediate the state characterized by control condition without any treatment to that of treatment and to depict the drug effects on molecules by the drug tokens. We applied EPN to our generated pairwise drug combination microarray data. The synergistic predictions using EPN are consistent with those predicted using phenotypic response data. The molecules responsible for the synergistic effects with their associated feedback loops display the mechanisms of synergism. The software implemented in Python 2.7 programming language is available from request. stwong@tmhs.org.

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.

Hepatic stellate cell and myofibroblast-like cell gene expression in the explanted cirrhotic livers of patients undergoing liver transplantation.

PubMed

Estep, J Michael; O'Reilly, Linda; Grant, Geraldine; Piper, James; Jonsson, Johann; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair M

2010-02-01

Hepatic stellate cells (HSC) are involved in hepatic fibrogenesis. Cell signaling associated with an insult to the liver affects an HSC transdifferentiation to fibrogenic myofibroblast-like cells. To investigate the transcriptional expression distinguishing HSC and myofibroblast-like cells between livers with and without cirrhosis. Tissue from ten cirrhotic livers (undergoing transplant) and four non-cirrhotic livers from the National Disease Research Interchange underwent cell separation to extract HSC and myofibroblast-like cell populations. Separated cell types as well as LI-90 cells were subjected to microarray analysis. Selected microarray results were verified by quantitative real-time PCR. Differential expression of some genes, such as IL-1beta, IL-1alpha, and IL-6, was associated with both transdifferentiation and disease. Other genes, such as fatty acid 2-hydroxylase only show differential expression in association with disease. Functional analysis supported these findings, indicating some signal transduction pathways (IL-6) are involved in disease and activation, whereas retinoid X receptor signaling in HSC from cirrhotic and non-cirrhotic livers varies in scope and quality. These findings indicate distinct phenotypes for HSC from cirrhotic and non-cirrhotic livers. Furthermore, coordinated differential expression between genes involved in the same signal transduction pathways provides some insight into the mechanisms that may control the balance between fibrogenesis and fibrolysis.

c-Kit modifies the inflammatory status of smooth muscle cells

PubMed Central

Song, Lei; Martinez, Laisel; Zigmond, Zachary M.; Hernandez, Diana R.; Lassance-Soares, Roberta M.; Selman, Guillermo

2017-01-01

Background c-Kit is a receptor tyrosine kinase present in multiple cell types, including vascular smooth muscle cells (SMC). However, little is known about how c-Kit influences SMC biology and vascular pathogenesis. Methods High-throughput microarray assays and in silico pathway analysis were used to identify differentially expressed genes between primary c-Kit deficient (KitW/W–v) and control (Kit+/+) SMC. Quantitative real-time RT-PCR and functional assays further confirmed the differences in gene expression and pro-inflammatory pathway regulation between both SMC populations. Results The microarray analysis revealed elevated NF-κB gene expression secondary to the loss of c-Kit that affects both the canonical and alternative NF-κB pathways. Upon stimulation with an oxidized phospholipid as pro-inflammatory agent, c-Kit deficient SMC displayed enhanced NF-κB transcriptional activity, higher phosphorylated/total p65 ratio, and increased protein expression of NF-κB regulated pro-inflammatory mediators with respect to cells from control mice. The pro-inflammatory phenotype of mutant cells was ameliorated after restoring c-Kit activity using lentiviral transduction. Functional assays further demonstrated that c-Kit suppresses NF-κB activity in SMC in a TGFβ-activated kinase 1 (TAK1) and Nemo-like kinase (NLK) dependent manner. Discussion Our study suggests a novel mechanism by which c-Kit suppresses NF-κB regulated pathways in SMC to prevent their pro-inflammatory transformation. PMID:28626608

c-Kit modifies the inflammatory status of smooth muscle cells.

PubMed

Song, Lei; Martinez, Laisel; Zigmond, Zachary M; Hernandez, Diana R; Lassance-Soares, Roberta M; Selman, Guillermo; Vazquez-Padron, Roberto I

2017-01-01

c-Kit is a receptor tyrosine kinase present in multiple cell types, including vascular smooth muscle cells (SMC). However, little is known about how c-Kit influences SMC biology and vascular pathogenesis. High-throughput microarray assays and in silico pathway analysis were used to identify differentially expressed genes between primary c-Kit deficient (Kit W/W-v ) and control (Kit +/+ ) SMC. Quantitative real-time RT-PCR and functional assays further confirmed the differences in gene expression and pro-inflammatory pathway regulation between both SMC populations. The microarray analysis revealed elevated NF-κB gene expression secondary to the loss of c-Kit that affects both the canonical and alternative NF-κB pathways. Upon stimulation with an oxidized phospholipid as pro-inflammatory agent, c-Kit deficient SMC displayed enhanced NF-κB transcriptional activity, higher phosphorylated/total p65 ratio, and increased protein expression of NF-κB regulated pro-inflammatory mediators with respect to cells from control mice. The pro-inflammatory phenotype of mutant cells was ameliorated after restoring c-Kit activity using lentiviral transduction. Functional assays further demonstrated that c-Kit suppresses NF-κB activity in SMC in a TGFβ-activated kinase 1 (TAK1) and Nemo-like kinase (NLK) dependent manner. Our study suggests a novel mechanism by which c-Kit suppresses NF-κB regulated pathways in SMC to prevent their pro-inflammatory transformation.

Functional characterization of MAT1-1-specific mating-type genes in the homothallic ascomycete Sordaria macrospora provides new insights into essential and nonessential sexual regulators.

PubMed

Klix, V; Nowrousian, M; Ringelberg, C; Loros, J J; Dunlap, J C; Pöggeler, S

2010-06-01

Mating-type genes in fungi encode regulators of mating and sexual development. Heterothallic ascomycete species require different sets of mating-type genes to control nonself-recognition and mating of compatible partners of different mating types. Homothallic (self-fertile) species also carry mating-type genes in their genome that are essential for sexual development. To analyze the molecular basis of homothallism and the role of mating-type genes during fruiting-body development, we deleted each of the three genes, SmtA-1 (MAT1-1-1), SmtA-2 (MAT1-1-2), and SmtA-3 (MAT1-1-3), contained in the MAT1-1 part of the mating-type locus of the homothallic ascomycete species Sordaria macrospora. Phenotypic analysis of deletion mutants revealed that the PPF domain protein-encoding gene SmtA-2 is essential for sexual reproduction, whereas the alpha domain protein-encoding genes SmtA-1 and SmtA-3 play no role in fruiting-body development. By means of cross-species microarray analysis using Neurospora crassa oligonucleotide microarrays hybridized with S. macrospora targets and quantitative real-time PCR, we identified genes expressed under the control of SmtA-1 and SmtA-2. Both genes are involved in the regulation of gene expression, including that of pheromone genes.

Functional Characterization of MAT1-1-Specific Mating-Type Genes in the Homothallic Ascomycete Sordaria macrospora Provides New Insights into Essential and Nonessential Sexual Regulators▿†

PubMed Central

Klix, V.; Nowrousian, M.; Ringelberg, C.; Loros, J. J.; Dunlap, J. C.; Pöggeler, S.

2010-01-01

Mating-type genes in fungi encode regulators of mating and sexual development. Heterothallic ascomycete species require different sets of mating-type genes to control nonself-recognition and mating of compatible partners of different mating types. Homothallic (self-fertile) species also carry mating-type genes in their genome that are essential for sexual development. To analyze the molecular basis of homothallism and the role of mating-type genes during fruiting-body development, we deleted each of the three genes, SmtA-1 (MAT1-1-1), SmtA-2 (MAT1-1-2), and SmtA-3 (MAT1-1-3), contained in the MAT1-1 part of the mating-type locus of the homothallic ascomycete species Sordaria macrospora. Phenotypic analysis of deletion mutants revealed that the PPF domain protein-encoding gene SmtA-2 is essential for sexual reproduction, whereas the α domain protein-encoding genes SmtA-1 and SmtA-3 play no role in fruiting-body development. By means of cross-species microarray analysis using Neurospora crassa oligonucleotide microarrays hybridized with S. macrospora targets and quantitative real-time PCR, we identified genes expressed under the control of SmtA-1 and SmtA-2. Both genes are involved in the regulation of gene expression, including that of pheromone genes. PMID:20435701

A phenotypic comparison of intervertebral disc and articular cartilage cells in the rat

PubMed Central

Lee, Cynthia R.; Sakai, Daisuke; Nakai, Tomoko; Toyama, Kanae; Mochida, Joji; Alini, Mauro

2007-01-01

The basic molecular characteristics of intervertebral disc cells are still poorly defined. This study compared the phenotypes of nucleus pulposus (NP), annulus fibrosus (AF) and articular cartilage (AC) cells using rat coccygeal discs and AC from both young and aged animals and a combination of microarray, real-time RT-PCR and immunohistochemistry. Microarray analysis identified 63 genes with at least a fivefold difference in fluorescence intensity between the NP and AF cells and 41 genes with a fivefold or greater difference comparing NP cells and articular chondrocytes. In young rats, the relative mRNA levels, assessed by real-time RT-PCR, of annexin A3, glypican 3 (gpc3), keratin 19 (k19) and pleiotrophin (ptn) were significantly higher in NP compared to AF and AC samples. Furthermore, vimentin (vim) mRNA was higher in NP versus AC, and expression levels of cartilage oligomeric matrix protein (comp) and matrix gla protein (mgp) were lower in NP versus AC. Higher NP levels of comp and mgp mRNA and higher AF levels of gpc3, k19, mgp and ptn mRNA were found in aged compared to young tissue. However, the large differences between NP and AC expression of gpc3 and k19 were obvious even in the aged animals. Furthermore, the differences in expression levels of gpc3 and k19 were also evident at the protein level, with intense immunostaining for both proteins in NP and non-existent immunoreaction in AF and AC. Future studies using different species are required to evaluate whether the expression of these molecules can be used to characterize NP cells and distinguish them from other chondrocyte-like cells. PMID:17786487

Gene Expression Patterns Associated With Histopathology in Toxic Liver Fibrosis.

PubMed

Ippolito, Danielle L; AbdulHameed, Mohamed Diwan M; Tawa, Gregory J; Baer, Christine E; Permenter, Matthew G; McDyre, Bonna C; Dennis, William E; Boyle, Molly H; Hobbs, Cheryl A; Streicker, Michael A; Snowden, Bobbi S; Lewis, John A; Wallqvist, Anders; Stallings, Jonathan D

2016-01-01

Toxic industrial chemicals induce liver injury, which is difficult to diagnose without invasive procedures. Identifying indicators of end organ injury can complement exposure-based assays and improve predictive power. A multiplexed approach was used to experimentally evaluate a panel of 67 genes predicted to be associated with the fibrosis pathology by computationally mining DrugMatrix, a publicly available repository of gene microarray data. Five-day oral gavage studies in male Sprague Dawley rats dosed with varying concentrations of 3 fibrogenic compounds (allyl alcohol, carbon tetrachloride, and 4,4'-methylenedianiline) and 2 nonfibrogenic compounds (bromobenzene and dexamethasone) were conducted. Fibrosis was definitively diagnosed by histopathology. The 67-plex gene panel accurately diagnosed fibrosis in both microarray and multiplexed-gene expression assays. Necrosis and inflammatory infiltration were comorbid with fibrosis. ANOVA with contrasts identified that 51 of the 67 predicted genes were significantly associated with the fibrosis phenotype, with 24 of these specific to fibrosis alone. The protein product of the gene most strongly correlated with the fibrosis phenotype PCOLCE (Procollagen C-Endopeptidase Enhancer) was dose-dependently elevated in plasma from animals administered fibrogenic chemicals (P < .05). Semiquantitative global mass spectrometry analysis of the plasma identified an additional 5 protein products of the gene panel which increased after fibrogenic toxicant administration: fibronectin, ceruloplasmin, vitronectin, insulin-like growth factor binding protein, and α2-macroglobulin. These results support the data mining approach for identifying gene and/or protein panels for assessing liver injury and may suggest bridging biomarkers for molecular mediators linked to histopathology. Published by Oxford University Press on behalf of the Society of Toxicology 2015. This work is written by US Government employees and is in the public domain in the US.

Molecular Diversity of Macrophages in Allergic Reaction: Comparison between the Allergenic Modes; Th1- and -Th2-Derived Immune Conditions.

PubMed

Bagheri, Mozhdeh; Dong, Yupeng; Ono, Masao

2015-06-01

Activated macrophages have been classified into classical (M1) and alternative (M2) macrophages. We aimed to establish a method to yield enough number of macrophages to analyze their molecular, biological and immunological functions. We used drugs; adjuvant albumin from chicken egg whites--Imject Alum (OVA-Alum) and OVA Complete Freund Adjuvant (OVA-CFA), to induce macrophages to M2 and M1 respectively. We analyzed the phenotype of purified macrophages induced under these immune conditions, using flow cytometry (FACS) to detect cell-surface molecules and the enzyme-linked immunosorbent assay (ELISA) was used to detect cytokines. The cDNA microarray was employed to measure changes in expression level of cell surface protein between M1 and M2 macrophages. Phenotype analysis of purified macrophages, induced under these immune conditions, showed macrophages induced by OVA-Alum was almost M2 while the proportion of M1 macrophages induced by OVA-CFA was significantly higher. The results also showed higher expression level of macrophage galactose N- acetyl-galactosamine specific lectin-2 protein (MGL1/2-PE), a known M2 macrophage marker, on the surface of Alum-induced macrophages. On the basis of these preliminary data, ELISA results revealed that after macrophage stimulation with lipopolysaccharides (LPS), the level of interleukin (IL)-10 produced by Alum- induced macrophages was higher than the level of IL-10 produced by CFA-induced macrophages. In contrast, the level of tumor necrosis factor-alpha (TNF-α) produced by CFA-induced macrophages was higher than Alum-induced macrophages. The cDNA microarray confirmed previous results and suggest immunoglobulin-like type 2 receptor alpha (Pilra) as a new marker for M1, macrophage galactose N-acetylgalactosamine-specific lectin 2 (Mgl2) as M2 macrophages marker.

Chromosomal microarray testing identifies a 4p terminal region associated with seizures in Wolf-Hirschhorn syndrome.

PubMed

Ho, Karen S; South, Sarah T; Lortz, Amanda; Hensel, Charles H; Sdano, Mallory R; Vanzo, Rena J; Martin, Megan M; Peiffer, Andreas; Lambert, Christophe G; Calhoun, Amy; Carey, John C; Battaglia, Agatino

2016-04-01

Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. Using chromosomal microarray analysis, we finely mapped the breakpoints of copy number variants (CNVs) in 48 individuals with WHS. Seizure phenotype data were collected through parent-reported answers to a comprehensive questionnaire and supplemented with available medical records. We observed a significant correlation between the presence of an interstitial 4p deletion and lack of a seizure phenotype (Fisher's exact test p=3.59e-6). In our cohort, there were five individuals with interstitial deletions with a distal breakpoint at least 751 kbp proximal to the 4p terminus. Four of these individuals have never had an observable seizure, and the fifth individual had a single febrile seizure at the age of 1.5 years. All other individuals in our cohort whose deletions encompass the terminal 751 kbp region report having seizures typical of WHS. Additional examples from the literature corroborate these observations and further refine the candidate seizure susceptibility region to a region 197 kbp in size, starting 368 kbp from the terminus of chromosome 4. We identify a small terminal region of chromosome 4p that represents a seizure susceptibility region. Deletion of this region in the context of WHS is sufficient for seizure occurrence. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Characterization of aldehyde dehydrogenase 1 high ovarian cancer cells: Towards targeted stem cell therapy.

PubMed

Sharrow, Allison C; Perkins, Brandy; Collector, Michael I; Yu, Wayne; Simons, Brian W; Jones, Richard J

2016-08-01

The cancer stem cell (CSC) paradigm hypothesizes that successful clinical eradication of CSCs may lead to durable remission for patients with ovarian cancer. Despite mounting evidence in support of ovarian CSCs, their phenotype and clinical relevance remain unclear. We and others have found high aldehyde dehydrogenase 1 (ALDH(high)) expression in a variety of normal and malignant stem cells, and sought to better characterize ALDH(high) cells in ovarian cancer. We compared ALDH(high) to ALDH(low) cells in two ovarian cancer models representing distinct subtypes: FNAR-C1 cells, derived from a spontaneous rat endometrioid carcinoma, and the human SKOV3 cell line (described as both serous and clear cell subtypes). We assessed these populations for stem cell features then analyzed expression by microarray and qPCR. ALDH(high) cells displayed CSC properties, including: smaller size, quiescence, regenerating the phenotypic diversity of the cell lines in vitro, lack of contact inhibition, nonadherent growth, multi-drug resistance, and in vivo tumorigenicity. Microarray and qPCR analysis of the expression of markers reported by others to enrich for ovarian CSCs revealed that ALDH(high) cells of both models showed downregulation of CD24, but inconsistent expression of CD44, KIT and CD133. However, the following druggable targets were consistently expressed in the ALDH(high) cells from both models: mTOR signaling, her-2/neu, CD47 and FGF18/FGFR3. Based on functional characterization, ALDH(high) ovarian cancer cells represent an ovarian CSC population. Differential gene expression identified druggable targets that have the potential for therapeutic efficacy against ovarian CSCs from multiple subtypes. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Karyotype versus microarray testing for genetic abnormalities after stillbirth.

PubMed

Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn

2012-12-06

Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

Copy number gain at 8q12.1-q22.1 is associated with a malignant tumor phenotype in salivary gland myoepitheliomas.

PubMed

Vékony, Hedy; Röser, Kerstin; Löning, Thomas; Ylstra, Bauke; Meijer, Gerrit A; van Wieringen, Wessel N; van de Wiel, Mark A; Carvalho, Beatriz; Kok, Klaas; Leemans, C René; van der Waal, Isaäc; Bloemena, Elisabeth

2009-02-01

Salivary gland myoepithelial tumors are relatively uncommon tumors with an unpredictable clinical course. More knowledge about their genetic profiles is necessary to identify novel predictors of disease. In this study, we subjected 27 primary tumors (15 myoepitheliomas and 12 myoepithelial carcinomas) to genome-wide microarray-based comparative genomic hybridization (array CGH). We set out to delineate known chromosomal aberrations in more detail and to unravel chromosomal differences between benign myoepitheliomas and myoepithelial carcinomas. Patterns of DNA copy number aberrations were analyzed by unsupervised hierarchical cluster analysis. Both benign and malignant tumors revealed a limited amount of chromosomal alterations (median of 5 and 7.5, respectively). In both tumor groups, high frequency gains (> or =20%) were found mainly at loci of growth factors and growth factor receptors (e.g., PDGF, FGF(R)s, and EGFR). In myoepitheliomas, high frequency losses (> or =20%) were detected at regions of proto-cadherins. Cluster analysis of the array CGH data identified three clusters. Differential copy numbers on chromosome arm 8q and chromosome 17 set the clusters apart. Cluster 1 contained a mixture of the two phenotypes (n = 10), cluster 2 included mostly benign tumors (n = 10), and cluster 3 only contained carcinomas (n = 7). Supervised analysis between malignant and benign tumors revealed a 36 Mbp-region at 8q being more frequently gained in malignant tumors (P = 0.007, FDR = 0.05). This is the first study investigating genomic differences between benign and malignant myoepithelial tumors of the salivary glands at a genomic level. Both unsupervised and supervised analysis of the genomic profiles revealed chromosome arm 8q to be involved in the malignant phenotype of salivary gland myoepitheliomas.

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

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

Closing the Phenotypic Gap between Transformed Neuronal Cell Lines in Culture and Untransformed Neurons

NASA Technical Reports Server (NTRS)

Myers, Tereance A.; Nickerson, Cheryl A.; Kaushal, Deepak; Ott, C. Mark; HonerzuBentrup, Kerstin; Ramamurthy, Rajee; Nelman-Gonzales, Mayra; Pierson, Duane L.; Philipp, Mario T.

2008-01-01

Studies of neuronal dysfunction in the central nervous system (CNS) are frequently limited by the failure of primary neurons to propagate in vitro. Neuronal cell lines can be substituted for primary cells but they often misrepresent normal conditions. We hypothesized that a dimensional (3-D) cell culture system would drive the phenotype of transformed neurons closer to that of untransformed cells. In our studies comparing 3-D versus 2-dimensional (2-D) culture, neuronal SH-SY5Y (SY) cells underwent distinct morphological changes combined with a significant drop in their rate of cell division. Expression of the proto-oncogene N-myc and the RNA binding protein HuD was decreased in 3-D culture as compared to standard 2-D conditions. We observed a decline in the anti-apoptotic protein Bcl-2 in 3-D culture, coupled with increased expression of the pro-apoptotic proteins Bax and Bak. Moreover, thapsigargin (TG)-induced apoptosis was enhanced in the 3-D cells. Microarray analysis demonstrated significantly differing mRNA levels for over 700 genes in the cells of each culture type. These results indicate that a 3-D culture approach narrows the phenotypic gap between neuronal cell lines and primary neurons. The resulting cells may readily be used for in vitro research of neuronal pathogenesis.

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

PubMed

Tra, Yolande V; Evans, Irene M

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

PubMed Central

Evans, Irene M.

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

The FLIGHT Drosophila RNAi database

PubMed Central

Bursteinas, Borisas; Jain, Ekta; Gao, Qiong; Baum, Buzz; Zvelebil, Marketa

2010-01-01

FLIGHT (http://flight.icr.ac.uk/) is an online resource compiling data from high-throughput Drosophila in vivo and in vitro RNAi screens. FLIGHT includes details of RNAi reagents and their predicted off-target effects, alongside RNAi screen hits, scores and phenotypes, including images from high-content screens. The latest release of FLIGHT is designed to enable users to upload, analyze, integrate and share their own RNAi screens. Users can perform multiple normalizations, view quality control plots, detect and assign screen hits and compare hits from multiple screens using a variety of methods including hierarchical clustering. FLIGHT integrates RNAi screen data with microarray gene expression as well as genomic annotations and genetic/physical interaction datasets to provide a single interface for RNAi screen analysis and datamining in Drosophila. PMID:20855970

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.

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

Zebrafish knockout of Down syndrome gene, DYRK1A, shows social impairments relevant to autism.

PubMed

Kim, Oc-Hee; Cho, Hyun-Ju; Han, Enna; Hong, Ted Inpyo; Ariyasiri, Krishan; Choi, Jung-Hwa; Hwang, Kyu-Seok; Jeong, Yun-Mi; Yang, Se-Yeol; Yu, Kweon; Park, Doo-Sang; Oh, Hyun-Woo; Davis, Erica E; Schwartz, Charles E; Lee, Jeong-Soo; Kim, Hyung-Goo; Kim, Cheol-Hee

2017-01-01

DYRK1A maps to the Down syndrome critical region at 21q22. Mutations in this kinase-encoding gene have been reported to cause microcephaly associated with either intellectual disability or autism in humans. Intellectual disability accompanied by microcephaly was recapitulated in a murine model by overexpressing Dyrk1a which mimicked Down syndrome phenotypes. However, given embryonic lethality in homozygous knockout (KO) mice, no murine model studies could present sufficient evidence to link Dyrk1a dysfunction with autism. To understand the molecular mechanisms underlying microcephaly and autism spectrum disorders (ASD), we established an in vivo dyrk1aa KO model using zebrafish. We identified a patient with a mutation in the DYRK1A gene using microarray analysis. Circumventing the barrier of murine model studies, we generated a dyrk1aa KO zebrafish using transcription activator-like effector nuclease (TALEN)-mediated genome editing. For social behavioral tests, we have established a social interaction test, shoaling assay, and group behavior assay. For molecular analysis, we examined the neuronal activity in specific brain regions of dyrk1aa KO zebrafish through in situ hybridization with various probes including c-fos and crh which are the molecular markers for stress response. Microarray detected an intragenic microdeletion of DYRK1A in an individual with microcephaly and autism. From behavioral tests of social interaction and group behavior, dyrk1aa KO zebrafish exhibited social impairments that reproduce human phenotypes of autism in a vertebrate animal model. Social impairment in dyrk1aa KO zebrafish was further confirmed by molecular analysis of c-fos and crh expression. Transcriptional expression of c-fos and crh was lower than that of wild type fish in specific hypothalamic regions, suggesting that KO fish brains are less activated by social context. In this study, we established a zebrafish model to validate a candidate gene for autism in a vertebrate animal. These results illustrate the functional deficiency of DYRK1A as an underlying disease mechanism for autism. We also propose simple social behavioral assays as a tool for the broader study of autism candidate genes.

Development of a high-throughput Candida albicans biofilm chip.

PubMed

Srinivasan, Anand; Uppuluri, Priya; Lopez-Ribot, Jose; Ramasubramanian, Anand K

2011-04-22

We have developed a high-density microarray platform consisting of nano-biofilms of Candida albicans. A robotic microarrayer was used to print yeast cells of C. albicans encapsulated in a collagen matrix at a volume as low as 50 nL onto surface-modified microscope slides. Upon incubation, the cells grow into fully formed "nano-biofilms". The morphological and architectural complexity of these biofilms were evaluated by scanning electron and confocal scanning laser microscopy. The extent of biofilm formation was determined using a microarray scanner from changes in fluorescence intensities due to FUN 1 metabolic processing. This staining technique was also adapted for antifungal susceptibility testing, which demonstrated that, similar to regular biofilms, cells within the on-chip biofilms displayed elevated levels of resistance against antifungal agents (fluconazole and amphotericin B). Thus, results from structural analyses and antifungal susceptibility testing indicated that despite miniaturization, these biofilms display the typical phenotypic properties associated with the biofilm mode of growth. In its final format, the C. albicans biofilm chip (CaBChip) is composed of 768 equivalent and spatially distinct nano-biofilms on a single slide; multiple chips can be printed and processed simultaneously. Compared to current methods for the formation of microbial biofilms, namely the 96-well microtiter plate model, this fungal biofilm chip has advantages in terms of miniaturization and automation, which combine to cut reagent use and analysis time, minimize labor intensive steps, and dramatically reduce assay costs. Such a chip should accelerate the antifungal drug discovery process by enabling rapid, convenient and inexpensive screening of hundreds-to-thousands of compounds simultaneously.

Building gene co-expression networks using transcriptomics data for systems biology investigations: Comparison of methods using microarray data

PubMed Central

Kadarmideen, Haja N; Watson-haigh, Nathan S

2012-01-01

Gene co-expression networks (GCN), built using high-throughput gene expression data are fundamental aspects of systems biology. The main aims of this study were to compare two popular approaches to building and analysing GCN. We use real ovine microarray transcriptomics datasets representing four different treatments with Metyrapone, an inhibitor of cortisol biosynthesis. We conducted several microarray quality control checks before applying GCN methods to filtered datasets. Then we compared the outputs of two methods using connectivity as a criterion, as it measures how well a node (gene) is connected within a network. The two GCN construction methods used were, Weighted Gene Co-expression Network Analysis (WGCNA) and Partial Correlation and Information Theory (PCIT) methods. Nodes were ranked based on their connectivity measures in each of the four different networks created by WGCNA and PCIT and node ranks in two methods were compared to identify those nodes which are highly differentially ranked (HDR). A total of 1,017 HDR nodes were identified across one or more of four networks. We investigated HDR nodes by gene enrichment analyses in relation to their biological relevance to phenotypes. We observed that, in contrast to WGCNA method, PCIT algorithm removes many of the edges of the most highly interconnected nodes. Removal of edges of most highly connected nodes or hub genes will have consequences for downstream analyses and biological interpretations. In general, for large GCN construction (with > 20000 genes) access to large computer clusters, particularly those with larger amounts of shared memory is recommended. PMID:23144540

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

Demonstration of a novel Xp22.2 microdeletion as the cause of familial extreme skewing of X-inactivation utilizing case-parent trio SNP microarray analysis.

PubMed

Mason, Jane A; Aung, Hnin T; Nandini, Adayapalam; Woods, Rickie G; Fairbairn, David J; Rowell, John A; Young, David; Susman, Rachel D; Brown, Simon A; Hyland, Valentine J; Robertson, Jeremy D

2018-05-01

We report a kindred referred for molecular investigation of severe hemophilia A in a young female in which extremely skewed X-inactivation was observed in both the proband and her clinically normal mother. Bidirectional Sanger sequencing of all F8 gene coding regions and exon/intron boundaries was undertaken. Methylation-sensitive restriction enzymes were utilized to investigate skewed X-inactivation using both a classical human androgen receptor (HUMARA) assay, and a novel method targeting differential methylation patterns in multiple informative X-chromosome SNPs. Illumina Whole-Genome Infinium microarray analysis was performed in the case-parent trio (proband and both parents), and the proband's maternal grandmother. The proband was a cytogenetically normal female with severe hemophilia A resulting from a heterozygous F8 pathogenic variant inherited from her similarly affected father. No F8 mutation was identified in the proband's mother, however, both the proband and her mother both demonstrated completely skewed X-chromosome inactivation (100%) in association with a previously unreported 2.3 Mb deletion at Xp22.2. At least three disease-associated genes (FANCB, AP1S2, and PIGA) were contained within the deleted region. We hypothesize that true "extreme" skewing of X-inactivation (≥95%) is a rare occurrence, but when defined correctly there is a high probability of finding an X-chromosome disease-causing variant or larger deletion resulting in X-inactivation through a survival disadvantage or cell lethal mechanism. We postulate that the 2.3 Mb Xp22.2 deletion identified in our kindred arose de novo in the proband's mother (on the grandfather's homolog), and produced extreme skewing of X-inactivation via a "cell lethal" mechanism. We introduce a novel multitarget approach for X-inactivation analysis using multiple informative differentially methylated SNPs, as an alternative to the classical single locus (HUMARA) method. We propose that for females with unexplained severe phenotypic expression of an X-linked recessive disorder trio-SNP microarray should be undertaken in combination with X-inactivation analysis. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

IFRD1 Is a Candidate Gene for SMNA on Chromosome 7q22-q23

PubMed Central

Brkanac, Zoran; Spencer, David; Shendure, Jay; Robertson, Peggy D.; Matsushita, Mark; Vu, Tiffany; Bird, Thomas D.; Olson, Maynard V.; Raskind, Wendy H.

2009-01-01

We have established strong linkage evidence that supports mapping autosomal-dominant sensory/motor neuropathy with ataxia (SMNA) to chromosome 7q22-q32. SMNA is a rare neurological disorder whose phenotype encompasses both the central and the peripheral nervous system. In order to identify a gene responsible for SMNA, we have undertaken a comprehensive genomic evaluation of the region of linkage, including evaluation for repeat expansion and small deletions or duplications, capillary sequencing of candidate genes, and massively parallel sequencing of all coding exons. We excluded repeat expansion and small deletions or duplications as causative, and through microarray-based hybrid capture and massively parallel short-read sequencing, we identified a nonsynonymous variant in the human interferon-related developmental regulator gene 1 (IFRD1) as a disease-causing candidate. Sequence conservation, animal models, and protein structure evaluation support the involvement of IFRD1 in SMNA. Mutation analysis of IFRD1 in additional patients with similar phenotypes is needed for demonstration of causality and further evaluation of its importance in neurological diseases. PMID:19409521

Def-6, a novel regulator of small GTPases in podocytes, acts downstream of atypical protein kinase C (aPKC) λ/ι.

PubMed

Worthmann, Kirstin; Leitges, Michael; Teng, Beina; Sestu, Marcello; Tossidou, Irini; Samson, Thomas; Haller, Hermann; Huber, Tobias B; Schiffer, Mario

2013-12-01

The atypical protein kinase C (aPKC) isotypes PKCλ/ι and PKCζ are both expressed in podocytes; however, little is known about differences in their function. Previous studies in mice have demonstrated that podocyte-specific loss of PKCλ/ι leads to a severe glomerular phenotype, whereas mice deficient in PKCζ develop no renal phenotype. We analyzed various effects caused by PKCλ/ι and PKCζ deficiency in cultured murine podocytes. In contrast to PKCζ-deficient podocytes, PKCλ/ι-deficient podocytes exhibited a severe actin cytoskeletal phenotype, reduced cell size, decreased number of focal adhesions, and increased activation of small GTPases. Comparative microarray analysis revealed that the guanine nucleotide exchange factor Def-6 was specifically up-regulated in PKCλ/ι-deficient podocytes. In vivo Def-6 expression is significantly increased in podocytes of PKCλ/ι-deficient mice. Cultured PKCλ/ι-deficient podocytes exhibited an enhanced membrane association of Def-6, indicating enhanced activation. Overexpression of aPKCλ/ι in PKCλ/ι-deficient podocytes could reduce the membrane-associated expression of Def-6 and rescue the actin phenotype. In the present study, PKCλ/ι was identified as an important factor for actin cytoskeletal regulation in podocytes and Def-6 as a specific downstream target of PKCλ/ι that regulates the activity of small GTPases and subsequently the actin cytoskeleton of podocytes. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2003-05-15

Understanding physiological control of osteoblast differentiation necessitates characterization of the regulatory signals that initiate the events directing a cell to lineage commitment and establishing competency for bone formation. The bone morphogenetic protein, BMP-2, a member of the TGFbeta superfamily, induces osteoblast differentiation and functions through the Smad signal transduction pathway during in vivo bone formation. However, the molecular targets of BMP-mediated gene transcription during the process of osteoblast differentiation have not been comprehensively identified. In the present study, BMP-2 responsive factors involved in the early stages of commitment and differentiation to the osteoblast phenotype were analyzed by microarray gene expression profiling in samples ranging from 1 to 24 h following BMP-2 dependent differentiation of C2C12 premyoblasts into the osteogenic lineage. A total of 1,800 genes were responsive to BMP-2 and expression was modulated from 3- to 14-fold for less than 100 genes during the time course. Approximately 50% of these 100 genes are either up- or downregulated. Major events associated with phenotypic changes towards the osteogenic lineage were identified from hierarchical and functional clustering analyses. BMP-2 immediately responsive genes (1-4 h), which exhibited either transient or sustained expression, reflect activation and repression of non-osseous BMP-2 developmental systems. This initial response was followed by waves of expression of nuclear proteins and developmental regulatory factors including inhibitors of DNA binding, Runx2, C/EBP, Zn finger binding proteins, forkhead, and numerous homeobox proteins (e.g., CDP/cut, paired, distaless, Hox) which are expressed at characterized stages during osteoblast differentiation. A sequential profile of genes mediating changes in cell morphology, cell growth, and basement membrane formation is observed as a secondary transient early response (2-8 h). Commitment to the osteogenic phenotype is recognized by 8 h, reflected by downregulation of most myogenic-related genes and induction of a spectrum of signaling proteins and enzymes facilitating synthesis and assembly of an extracellular skeletal environment. These genes included collagens Type I and VI and the small leucine rich repeat family of proteoglycans (e.g., decorin, biglycan, osteomodulin, fibromodulin, and osteoadherin/osteoglycin) that reached peak expression at 24 h. With extracellular matrix development, the bone phenotype was further established from 16 to 24 h by induction of genes for cell adhesion and communication and enzymes that organize the bone ECM. Our microarray analysis resulted in the discovery of a class of genes, initially described in relation to differentiation of astrocytes and oligodendrocytes that are functionally coupled to signals for cellular extensions. They include nexin, neuropilin, latexin, neuroglian, neuron specific gene 1, and Ulip; suggesting novel roles for these genes in the bone microenvironment. This global analysis identified a multistage molecular and cellular cascade that supports BMP-2-mediated osteoblast differentiation. Copyright 2003 Wiley-Liss, Inc.

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

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

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

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

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

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

Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier.

PubMed

Martins, Filipe C; Santiago, Ines de; Trinh, Anne; Xian, Jian; Guo, Anne; Sayal, Karen; Jimenez-Linan, Mercedes; Deen, Suha; Driver, Kristy; Mack, Marie; Aslop, Jennifer; Pharoah, Paul D; Markowetz, Florian; Brenton, James D

2014-12-17

TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events. Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort. PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.

Molecular Insights on Post-chemotherapy Retinoblastoma by Microarray Gene Expression Analysis

PubMed Central

Nalini, Venkatesan; Segu, Ramya; Deepa, Perinkulam Ravi; Khetan, Vikas; Vasudevan, Madavan; Krishnakumar, Subramanian

2013-01-01

Purpose Management of Retinoblastoma (RB), a pediatric ocular cancer is limited by drug-resistance and drug-dosage related side effects during chemotherapy. Molecular de-regulation in post-chemotherapy RB tumors was investigated. Materials and Methods cDNA microarray analysis of two post-chemotherapy and one pre-chemotherapy RB tumor tissues was performed, followed by Principle Component Analysis, Gene ontology, Pathway Enrichment analysis and Biological Analysis Network (BAN) modeling. The drug modulation role of two significantly up-regulated genes (p≤0.05) − Ect2 (Epithelial-cell-transforming-sequence-2), and PRAME (preferentially-expressed-Antigen-in-Melanoma) was assessed by qRT-PCR, immunohistochemistry and cell viability assays. Results Differential up-regulation of 1672 genes and down-regulation of 2538 genes was observed in RB tissues (relative to normal adult retina), while 1419 genes were commonly de-regulated between pre-chemotherapy and post- chemotherapy RB. Twenty one key gene ontology categories, pathways, biomarkers and phenotype groups harboring 250 differentially expressed genes were dys-regulated (EZH2, NCoR1, MYBL2, RB1, STAMN1, SYK, JAK1/2, STAT1/2, PLK2/4, BIRC5, LAMN1, Ect2, PRAME and ABCC4). Differential molecular expressions of PRAME and Ect2 in RB tumors with and without chemotherapy were analyzed. There was neither up- regulation of MRP1, nor any significant shift in chemotherapeutic IC50, in PRAME over-expressed versus non-transfected RB cells. Conclusion Cell cycle regulatory genes were dys-regulated post-chemotherapy. Ect2 gene was expressed in response to chemotherapy-induced stress. PRAME does not contribute to drug resistance in RB, yet its nuclear localization and BAN information, points to its possible regulatory role in RB. PMID:24092970

Correlation of gene expression with bladder capacity in interstitial cystitis/bladder pain syndrome.

PubMed

Colaco, Marc; Koslov, David S; Keys, Tristan; Evans, Robert J; Badlani, Gopal H; Andersson, Karl-Erik; Walker, Stephen J

2014-10-01

Interstitial cystitis and bladder pain syndrome are terms used to describe a heterogeneous chronic pelvic and bladder pain disorder. Despite its significant prevalence, our understanding of disease etiology is poor. We molecularly characterized interstitial cystitis/bladder pain syndrome and determined whether there are clinical factors that correlate with gene expression. Bladder biopsies from female subjects with interstitial cystitis/bladder pain syndrome and female controls without signs of the disease were collected and divided into those with normal and low anesthetized bladder capacity, respectively. Samples then underwent RNA extraction and microarray assay. Data generated by these assays were analyzed using Omics Explorer (Qlucore, Lund, Sweden), GeneSifter® Analysis Edition 4.0 and Ingenuity® Pathway Analysis to determine similarity among samples within and between groups, and measure differentially expressed transcripts unique to each phenotype. A total of 16 subjects were included in study. Principal component analysis and unsupervised hierarchical clustering showed clear separation between gene expression in tissues from subjects with low compared to normal bladder capacity. Gene expression in tissue from patients with interstitial cystitis/bladder pain syndrome who had normal bladder capacity did not significantly differ from that in controls without interstitial cystitis/bladder pain syndrome. Pairwise analysis revealed that pathways related to inflammatory and immune response were most involved. Microarray analysis provides insight into the potential pathological condition underlying interstitial cystitis/bladder pain syndrome. This pilot study shows that patients with this disorder who have low compared to normal bladder capacity have significantly different molecular characteristics, which may reflect a difference in disease pathophysiology. Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

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

Improving diagnosis and broadening the phenotypes in early-onset seizure and severe developmental delay disorders through gene panel analysis.

PubMed

Trump, Natalie; McTague, Amy; Brittain, Helen; Papandreou, Apostolos; Meyer, Esther; Ngoh, Adeline; Palmer, Rodger; Morrogh, Deborah; Boustred, Christopher; Hurst, Jane A; Jenkins, Lucy; Kurian, Manju A; Scott, Richard H

2016-05-01

We sought to investigate the diagnostic yield and mutation spectrum in previously reported genes for early-onset epilepsy and disorders of severe developmental delay. In 400 patients with these disorders with no known underlying aetiology and no major structural brain anomaly, we analysed 46 genes using a combination of targeted sequencing on an Illumina MiSeq platform and targeted, exon-level microarray copy number analysis. We identified causative mutations in 71/400 patients (18%). The diagnostic rate was highest among those with seizure onset within the first two months of life (39%), although overall it was similar in those with and without seizures. The most frequently mutated gene was SCN2A (11 patients, 3%). Other recurrently mutated genes included CDKL5, KCNQ2, SCN8A (six patients each), FOXG1, MECP2, SCN1A, STXBP1 (five patients each), KCNT1, PCDH19, TCF4 (three patients each) and ATP1A3, PRRT2 and SLC9A6 (two patients each). Mutations in EHMT1, GABRB3, LGI1, MBD5, PIGA, UBE3A and ZEB2 were each found in single patients. We found mutations in a number of genes in patients where either the electroclinical features or dysmorphic phenotypes were atypical for the identified gene. In only 11 cases (15%) had the clinician sufficient certainty to specify the mutated gene as the likely cause before testing. Our data demonstrate the considerable utility of a gene panel approach in the diagnosis of patients with early-onset epilepsy and severe developmental delay disorders., They provide further insights into the phenotypic spectrum and genotype-phenotype correlations for a number of the causative genes and emphasise the value of exon-level copy number testing in their analysis. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

2016-01-01

Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

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

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

Chromosomal loss of 3q26.3-3q26.32, involving a partial neuroligin 1 deletion, identified by genomic microarray in a child with microcephaly, seizure disorder, and severe intellectual disability.

PubMed

Millson, Alison; Lagrave, Danielle; Willis, Mary J H; Rowe, Leslie R; Lyon, Elaine; South, Sarah T

2012-01-01

Neuroligin 1 (NLGN1) is one of five members of the neuroligin gene family and may represent a candidate gene for neurological disorders, as members of this family are involved in formation and remodeling of central nervous system synapses. NLGN1 is expressed predominantly in the central nervous system, where it dimerizes and then binds with β-neurexin to form a functional synapse. Mutations in neurexin 1 (NRXN1) as well as two other members of the neuroligin family, NLGN3 and NLGN4, have been associated with autism and mutations in NLGN4 have also been associated with intellectual disability, seizures, and EEG abnormalities. Genomic microarray is recommended for the detection of chromosomal gains or losses in patients with intellectual disability and multiple congenital anomalies. Results of uncertain significance are not uncommon. Parental studies can provide additional information by demonstrating that the imbalance is either de novo or inherited, and therefore is more or less likely to be causative of the clinical phenotype. However, the possibility that even inherited deletions and duplications may play a role in the phenotype of the proband cannot be excluded as many copy number variants associated with neurodevelopmental conditions show incomplete penetrance and may be inherited from an unaffected parent. Here, we report on a patient with a 2.2 Mb deletion at 3q26.3-3q26.32-encompassing the terminal end of NLGN1 and the entire NAALADL2 gene-detected by genomic microarray, and confirmed by FISH and real-time quantitative PCR. The same size deletion was subsequently found in her healthy, asymptomatic, adult mother. Copyright © 2011 Wiley Periodicals, Inc.

Involvement of Auxin and Brassinosteroid in Dwarfism of Autotetraploid Apple (Malus × domestica).

PubMed

Ma, Yue; Xue, Hao; Zhang, Lei; Zhang, Feng; Ou, Chunqing; Wang, Feng; Zhang, Zhihong

2016-05-24

The plant height is an important trait in fruit tree. However, the molecular mechanism on dwarfism is still poorly understood. We found that colchicine-induced autotetraploid apple plants (Malus × domestica) exhibited a dwarf phenotype. The vertical length of cortical parenchyma cells was shorter in autotetraploids than in diploids, by observing paraffin sections. Hormone levels of indoleacetic acid (IAA) and brassinosteroid (BR) were significantly decreased in 3- and 5-year-old autotetraploid plants. Digital gene expression (DGE) analysis showed that the differentially expressed genes were mainly involved in IAA and BR pathways. microRNA390 was significantly upregulated according to microarray analysis. Exogenous application of IAA and BR promoted stem elongation of both apple plants grown in medium. The results show that dwarfing in autotetraploid apple plants is most likely regulated by IAA and BR. The dwarf phenotype of autotetraploid apple plants could be due to accumulation of miR390 after genome doubling, leading to upregulation of apple trans-acting short-interfering RNA 3 (MdTAS3) expression, which in turn downregulates the expression of MdARF3. Overall, this leads to partial interruption of the IAA and BR signal transduction pathway. Our study provides important insights into the molecular mechanisms underlying dwarfism in autopolyploid apple plants.

Involvement of Auxin and Brassinosteroid in Dwarfism of Autotetraploid Apple (Malus × domestica)

PubMed Central

Ma, Yue; Xue, Hao; Zhang, Lei; Zhang, Feng; Ou, Chunqing; Wang, Feng; Zhang, Zhihong

2016-01-01

The plant height is an important trait in fruit tree. However, the molecular mechanism on dwarfism is still poorly understood. We found that colchicine-induced autotetraploid apple plants (Malus × domestica) exhibited a dwarf phenotype. The vertical length of cortical parenchyma cells was shorter in autotetraploids than in diploids, by observing paraffin sections. Hormone levels of indoleacetic acid (IAA) and brassinosteroid (BR) were significantly decreased in 3- and 5-year-old autotetraploid plants. Digital gene expression (DGE) analysis showed that the differentially expressed genes were mainly involved in IAA and BR pathways. microRNA390 was significantly upregulated according to microarray analysis. Exogenous application of IAA and BR promoted stem elongation of both apple plants grown in medium. The results show that dwarfing in autotetraploid apple plants is most likely regulated by IAA and BR. The dwarf phenotype of autotetraploid apple plants could be due to accumulation of miR390 after genome doubling, leading to upregulation of apple trans-acting short-interfering RNA 3 (MdTAS3) expression, which in turn downregulates the expression of MdARF3. Overall, this leads to partial interruption of the IAA and BR signal transduction pathway. Our study provides important insights into the molecular mechanisms underlying dwarfism in autopolyploid apple plants. PMID:27216878

PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

EPA Science Inventory

Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

Identification and characterization of nuclear genes involved in photosynthesis in Populus

PubMed Central

2014-01-01

Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936

A familial pericentric inversion of chromosome 11 associated with a microdeletion of 163 kb and microduplication of 288 kb at 11p13 and 11q22.3 without aniridia or eye anomalies.

PubMed

Balay, Lara; Totten, Ellen; Okada, Luna; Zell, Sidney; Ticho, Benjamin; Israel, Jeannette; Kogan, Jillene

2016-01-01

Interstitial deletions of 11p13 involving MPPED2, DCDC5, DCDC1, DNAJC24, IMMP1L, and ELP4 are previously reported to have downstream transcriptional effects on the expression of PAX6, due to a downstream regulatory region (DRR). Currently, no clear genotype-phenotype correlations have been established allowing for conclusive information regarding the exact location of the PAX6 DRR, though its location has been approximated in mouse models to be within the Elp4 gene. Of the clinical reports currently published examining patients with intact PAX6 genes but harboring deletions identified in genes downstream of PAX6, 100% indicate phenotypes which include aniridia, whereas approximately half report additional eye deformities, autism, or intellectual disability. In this clinical report, we present a 12-year-old male patient, his brother, and mother with pericentric inversions of chromosome 11 associated with submicroscopic interstitial deletions of 11p13 and duplications of 11q22.3. The inversions were identified by standard cytogenetic analysis; microarray and FISH detected the chromosomal imbalance. The patient's phenotype includes intellectual disability, speech abnormalities, and autistic behaviors, but interestingly neither the patient, his brother, nor mother have aniridia or other eye anomalies. To the best of our knowledge, these findings in three family members represent the only reported cases with 11p13 deletions downstream of PAX6 not demonstrating phenotypic characteristics of aniridia or abnormal eye development. Although none of the deleted genes are obvious candidates for the patient's phenotype, the absence of aniridia in the presence of this deletion in all three family members further delineates the location of the DRR for PAX6. © 2015 Wiley Periodicals, Inc.

Involvement of Pinus taeda MYB1 and MYB8 in phenylpropanoid metabolism and secondary cell wall biogenesis: a comparative in planta analysis

PubMed Central

Bomal, Claude; Bedon, Frank; Caron, Sébastien; Mansfield, Shawn D.; Levasseur, Caroline; Cooke, Janice E. K.; Blais, Sylvie; Tremblay, Laurence; Morency, Marie-Josée; Pavy, Nathalie; Grima-Pettenati, Jacqueline; Séguin, Armand; MacKay, John

2008-01-01

The involvement of two R2R3-MYB genes from Pinus taeda L., PtMYB1 and PtMYB8, in phenylpropanoid metabolism and secondary cell wall biogenesis was investigated in planta. These pine MYBs were constitutively overexpressed (OE) in Picea glauca (Moench) Voss, used as a heterologous conifer expression system. Morphological, histological, chemical (lignin and soluble phenols), and transcriptional analyses, i.e. microarray and reverse transcription quantitative PCR (RT-qPCR) were used for extensive phenotyping of MYB-overexpressing spruce plantlets. Upon germination of somatic embryos, root growth was reduced in both transgenics. Enhanced lignin deposition was also a common feature but ectopic secondary cell wall deposition was more strongly associated with PtMYB8-OE. Microarray and RT-qPCR data showed that overexpression of each MYB led to an overlapping up-regulation of many genes encoding phenylpropanoid enzymes involved in lignin monomer synthesis, while misregulation of several cell wall-related genes and other MYB transcription factors was specifically associated with PtMYB8-OE. Together, the results suggest that MYB1 and MYB8 may be part of a conserved transcriptional network involved in secondary cell wall deposition in conifers. PMID:18805909

Gene expression analysis of microtubule affinity-regulating kinase 2 in non-small cell lung cancer.

PubMed

Marshall, Erin A; Ng, Kevin W; Anderson, Christine; Hubaux, Roland; Thu, Kelsie L; Lam, Wan L; Martinez, Victor D

2015-12-01

Lung cancer is the leading cause of cancer death worldwide, and has a five-year survival rate of 18% [1]. MARK2 is a serine/threonine-protein kinase, and is a key component in the phosphorylation of microtubule-associated proteins [2], [3]. A recent study published by Hubaux et al. found that microtubule affinity-regulating kinase 2 (MARK2) showed highly frequent DNA and RNA level disruption in lung cancer cell lines and independent non-small cell lung cancer (NSCLC) cohorts [4]. These alterations result in the acquisition of oncogenic properties in cell lines, such as increased viability and anchorage-independent growth. Furthermore, a microarray-based transcriptome analysis of three short hairpin RNA (shRNA)-mediated MARK2 knockdown lung adenocarcinoma cell lines (GEO#: GSE57966) revealed an association between MARK2 gene expression and cell cycle activation and DNA damage response. Here, we present a detailed description of transcriptome analysis to support the described role of MARK2 in promoting a malignant phenotype.

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/.

Genomic Characterization of Variable Surface Antigens Reveals a Telomere Position Effect as a Prerequisite for RNA Interference-Mediated Silencing in Paramecium tetraurelia

PubMed Central

Baranasic, Damir; Oppermann, Timo; Cheaib, Miriam; Cullum, John; Schmidt, Helmut

2014-01-01

ABSTRACT Antigenic or phenotypic variation is a widespread phenomenon of expression of variable surface protein coats on eukaryotic microbes. To clarify the mechanism behind mutually exclusive gene expression, we characterized the genetic properties of the surface antigen multigene family in the ciliate Paramecium tetraurelia and the epigenetic factors controlling expression and silencing. Genome analysis indicated that the multigene family consists of intrachromosomal and subtelomeric genes; both classes apparently derive from different gene duplication events: whole-genome and intrachromosomal duplication. Expression analysis provides evidence for telomere position effects, because only subtelomeric genes follow mutually exclusive transcription. Microarray analysis of cultures deficient in Rdr3, an RNA-dependent RNA polymerase, in comparison to serotype-pure wild-type cultures, shows cotranscription of a subset of subtelomeric genes, indicating that the telomere position effect is due to a selective occurrence of Rdr3-mediated silencing in subtelomeric regions. We present a model of surface antigen evolution by intrachromosomal gene duplication involving the maintenance of positive selection of structurally relevant regions. Further analysis of chromosome heterogeneity shows that alternative telomere addition regions clearly affect transcription of closely related genes. Consequently, chromosome fragmentation appears to be of crucial importance for surface antigen expression and evolution. Our data suggest that RNAi-mediated control of this genetic network by trans-acting RNAs allows rapid epigenetic adaptation by phenotypic variation in combination with long-term genetic adaptation by Darwinian evolution of antigen genes. PMID:25389173

Role of Insulin-Like Growth Factor-1 Signaling Pathway in Cisplatin-Resistant Lung Cancer Cells

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

Sun Yunguang; Zheng Siyuan; Torossian, Artour

2012-03-01

Purpose: The development of drug-resistant phenotypes has been a major obstacle to cisplatin use in non-small-cell lung cancer. We aimed to identify some of the molecular mechanisms that underlie cisplatin resistance using microarray expression analysis. Methods and Materials: H460 cells were treated with cisplatin. The differences between cisplatin-resistant lung cancer cells and parental H460 cells were studied using Western blot, MTS, and clonogenic assays, in vivo tumor implantation, and microarray analysis. The cisplatin-R cells were treated with human recombinant insulin-like growth factor (IGF) binding protein-3 and siRNA targeting IGF-1 receptor. Results: Cisplatin-R cells illustrated greater expression of the markers CD133more » and aldehyde dehydrogenase, more rapid in vivo tumor growth, more resistance to cisplatin- and etoposide-induced apoptosis, and greater survival after treatment with cisplatin or radiation than the parental H460 cells. Also, cisplatin-R demonstrated decreased expression of insulin-like growth factor binding protein-3 and increased activation of IGF-1 receptor signaling compared with parental H460 cells in the presence of IGF-1. Human recombinant IGF binding protein-3 reversed cisplatin resistance in cisplatin-R cells and targeting of IGF-1 receptor using siRNA resulted in sensitization of cisplatin-R-cells to cisplatin and radiation. Conclusions: The IGF-1 signaling pathway contributes to cisplatin-R to cisplatin and radiation. Thus, this pathway represents a potential target for improved lung cancer response to treatment.« less

Molecular Analysis of Endocrine Disruption in Hornyhead Turbot at Wastewater Outfalls in Southern California Using a Second Generation Multi-Species Microarray

PubMed Central

Baker, Michael E.; Vidal-Dorsch, Doris E.; Ribecco, Cataldo; Sprague, L. James; Angert, Mila; Lekmine, Narimene; Ludka, Colleen; Martella, Andrea; Ricciardelli, Eugenia; Bay, Steven M.; Gully, Joseph R.; Kelley, Kevin M.; Schlenk, Daniel; Carnevali, Oliana; Šášik, Roman; Hardiman, Gary

2013-01-01

Sentinel fish hornyhead turbot ( Pleuronichthys verticalis ) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences. PMID:24086568

Microarray-based bioinformatics analysis of the combined effects of SiNPs and PbAc on cardiovascular system in zebrafish.

PubMed

Hu, Hejing; Zhang, Yannan; Shi, Yanfeng; Feng, Lin; Duan, Junchao; Sun, Zhiwei

2017-10-01

With rapid development of nanotechnology and growing environmental pollution, the combined toxic effects of SiNPs and pollutants of heavy metals like lead have received global attentions. The aim of this study was to explore the cardiovascular effects of the co-exposure of SiNPs and lead acetate (PbAc) in zebrafish using microarray and bioinformatics analysis. Although there was no other obvious cardiovascular malformation except bleeding phenotype, bradycardia, angiogenesis inhibition and declined cardiac output in zebrafish co-exposed of SiNPs and PbAc at NOAEL level, significant changes were observed in mRNA and microRNA (miRNA) expression patterns. STC-GO analysis indicated that the co-exposure might have more toxic effects on cardiovascular system than that exposure alone. Key differentially expressed genes were discerned out based on the Dynamic-gene-network, including stxbp1a, ndfip2, celf4 and gsk3b. Furthermore, several miRNAs obtained from the miRNA-Gene-Network might play crucial roles in cardiovascular disease, such as dre-miR-93, dre-miR-34a, dre-miR-181c, dre-miR-7145, dre-miR-730, dre-miR-129-5p, dre-miR-19d, dre-miR-218b, dre-miR-221. Besides, the analysis of miRNA-pathway-network indicated that the zebrafish were stimulated by the co-exposure of SiNPs and PbAc, which might cause the disturbance of calcium homeostasis and endoplasmic reticulum stress. As a result, cardiac muscle contraction might be deteriorated. In general, our data provide abundant fundamental research clues to the combined toxicity of environmental pollutants and further in-depth verifications are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Nonmosaic tetrasomy 15q25.2 → qter identified with SNP microarray in a patient with characteristic facial appearance and review of the literature.

PubMed

Xu, Huihui; Xiao, Bing; Ji, Xing; Hu, Qin; Chen, Yingwei; Qiu, Wenjuan

2014-07-01

Tetrasomy for the distal chromosome 15q is rare, and only 22 patients (including 6 cases without detailed information) have been described to date in the literature. Here we report on another patient with nonmosaic tetrasomy 15q25.2-qter resulted from an inverted duplication of distal chromosome 15. This patient presents with features of development delay, arachnodactyly, joint contractures and typical facial dysmorphism including frontal bossing, short palpebral fissures, long philtrum, low-set ears, high-arched palate and retrognathia. Unlike most of the related patients, abdominal ultrasound test and brain MRI showed normal. Karyotyping analysis revealed a supernumerary marker chromosome presented in all metaphase cells examined. Parental karyotyping analysis was normal, indicating a de novo chromosome aberration of the patient. SNP microarray analysis found a two copy gain of 17.7 Mb from the distal long arm of chromosome 15 (15q25.2-qter). Further FISH analysis using SureFISH 15q26.3 IGF1R probe proved an inverted duplication of distal long arm of chromosome 15. The segmental duplications which lie in the hotspots of 15q24-26 might increase the susceptibility of chromosome rearrangement. Compared with the George-Abraham' study [2012], ADAMTSL3 might be more related to the cardiac disorders in tetrasomy 15q patients. Considering all patients reported in the literature, different mosaic degrees and segmental sizes don't correlate to the severity of phenotypes. A clear delineation on tetrasomy for distal chromosome 15q could still be investigated. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Potential upstream regulators of cannabinoid receptor 1 signaling in prostate cancer: a Bayesian network analysis of data from a tissue microarray.

PubMed

Häggström, Jenny; Cipriano, Mariateresa; Forshell, Linus Plym; Persson, Emma; Hammarsten, Peter; Stella, Nephi; Fowler, Christopher J

2014-08-01

The endocannabinoid system regulates cancer cell proliferation, and in prostate cancer a high cannabinoid CB1 receptor expression is associated with a poor prognosis. Down-stream mediators of CB1 receptor signaling in prostate cancer are known, but information on potential upstream regulators is lacking. Data from a well-characterized tumor tissue microarray were used for a Bayesian network analysis using the max-min hill-climbing method. In non-malignant tissue samples, a directionality of pEGFR (the phosphorylated form of the epidermal growth factor receptor) → CB1 receptors were found regardless as to whether the endocannabinoid metabolizing enzyme fatty acid amide hydrolase (FAAH) was included as a parameter. A similar result was found in the tumor tissue, but only when FAAH was included in the analysis. A second regulatory pathway, from the growth factor receptor ErbB2 → FAAH was also identified in the tumor samples. Transfection of AT1 prostate cancer cells with CB1 receptors induced a sensitivity to the growth-inhibiting effects of the CB receptor agonist CP55,940. The sensitivity was not dependent upon the level of receptor expression. Thus a high CB1 receptor expression alone does not drive the cells towards a survival phenotype in the presence of a CB receptor agonist. The data identify two potential regulators of the endocannabinoid system in prostate cancer and allow the construction of a model of a dysregulated endocannabinoid signaling network in this tumor. Further studies should be designed to test the veracity of the predictions of the network analysis in prostate cancer and other solid tumors. © 2014 The Authors. The Prostate published by Wiley Periodicals, Inc.

Nanotechnology: moving from microarrays toward nanoarrays.

PubMed

Chen, Hua; Li, Jun

2007-01-01

Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

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.

A link among DNA replication, recombination, and gene expression revealed by genetic and genomic analysis of TEBICHI gene of Arabidopsis thaliana.

PubMed

Inagaki, Soichi; Nakamura, Kenzo; Morikami, Atsushi

2009-08-01

Spatio-temporal regulation of gene expression during development depends on many factors. Mutations in Arabidopsis thaliana TEBICHI (TEB) gene encoding putative helicase and DNA polymerase domains-containing protein result in defects in meristem maintenance and correct organ formation, as well as constitutive DNA damage response and a defect in cell cycle progression; but the molecular link between these phenotypes of teb mutants is unknown. Here, we show that mutations in the DNA replication checkpoint pathway gene, ATR, but not in ATM gene, enhance developmental phenotypes of teb mutants, although atr suppresses cell cycle defect of teb mutants. Developmental phenotypes of teb mutants are also enhanced by mutations in RAD51D and XRCC2 gene, which are involved in homologous recombination. teb and teb atr double mutants exhibit defects in adaxial-abaxial polarity of leaves, which is caused in part by the upregulation of ETTIN (ETT)/AUXIN RESPONSIVE FACTOR 3 (ARF3) and ARF4 genes. The Helitron transposon in the upstream of ETT/ARF3 gene is likely to be involved in the upregulation of ETT/ARF3 in teb. Microarray analysis indicated that teb and teb atr causes preferential upregulation of genes nearby the Helitron transposons. Furthermore, interestingly, duplicated genes, especially tandemly arrayed homologous genes, are highly upregulated in teb or teb atr. We conclude that TEB is required for normal progression of DNA replication and for correct expression of genes during development. Interplay between these two functions and possible mechanism leading to altered expression of specific genes will be discussed.

Transcriptome Analysis of Human Injured Meniscus Reveals a Distinct Phenotype of Meniscus Degeneration with Aging

PubMed Central

Rai, Muhammad Farooq; Patra, Debabrata; Sandell, Linda J.; Brophy, Robert H.

2013-01-01

Objective Meniscus tears are associated with a heightened risk for osteoarthritis. We aimed to advance our understanding of the metabolic state of human injured meniscus at the time of arthroscopic partial meniscectomy through transcriptome-wide analysis of gene expression in relation to patient age and degree of cartilage chondrosis. Methods The degree of chondrosis of knee cartilage was recorded at the time of meniscectomy in symptomatic patients without radiographic osteoarthritis. RNA preparations from resected menisci (N=12) were subjected to transcriptome-wide microarray and QuantiGene Plex analyses. The relative changes in gene expression variation with age and chondrosis were analyzed and integrated biological processes were investigated computationally. Results We identified a set of genes in torn meniscus that were differentially expressed with age and chondrosis. There were 866 genes differentially regulated (≥1.5-fold; P<0.05) with age and 49 with chondrosis. In older patients, genes associated with cartilage and skeletal development and extracellular matrix synthesis were repressed while those involved in immune response, inflammation, cell cycle, and cellular proliferation were stimulated. With chondrosis, genes representing cell catabolism (cAMP catabolic process) and tissue and endothelial cell development were repressed and those involved in T cell differentiation and apoptosis were elevated. Conclusion Differences in age-related gene expression suggest that in older adults, meniscal cells might de-differentiate and initiate a proliferative phenotype. Conversely, meniscal cells in younger patients appear to respond to injury, but maintain the differentiated phenotype. Definitive molecular signatures identified in damaged meniscus could be segregated largely with age and, to a lesser extent, with chondrosis. PMID:23658108

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

Maternal Gametic Transmission of Translocations or Inversions of Human Chromosome 11p15.5 Results in Regional DNA Hypermethylation and Downregulation of CDKN1C Expression

PubMed Central

Smith, Adam C.; Suzuki, Masako; Thompson, Reid; Choufani, Sanaa; Higgins, Michael J.; Chiu, Idy W.; Squire, Jeremy A.; Greally, John M.; Weksberg, Rosanna

2015-01-01

Beckwith-Wiedemann syndrome (BWS) is an overgrowth syndrome associated with genetic or epigenetic alterations in one of two imprinted domains on chromosome 11p15.5. Rarely, chromosomal translocations or inversions of chromosome 11p15.5 are associated with BWS but the molecular pathophysiology in such cases is not understood. In our series of 3 translocation and 2 inversion patients with BWS, the chromosome 11p15.5 breakpoints map within the centromeric imprinted domain, 2. We hypothesized that either microdeletions/microduplications adjacent to the breakpoints could disrupt genomic sequences important for imprinted gene regulation. An alternate hypothesis was that epigenetic alterations of as yet unknown regulatory DNA sequences, result in the BWS phenotype. A high resolution Nimblegen custom microarray was designed representing all non-repetitive sequences in the telomeric 33 MB of the short arm of human chromosome 11. For the BWS-associated chromosome 11p15.5 translocations and inversions, we found no evidence of microdeletions/microduplications. DNA methylation was also tested on this microarray using the HpaII tiny fragment enrichment by ligation-mediated PCR (HELP) assay. This high-resolution DNA methylation microarray analysis revealed a gain of DNA methylation in the translocation/inversion patients affecting the p-ter segment of chromosome 11p15, including both imprinted domains. BWS patients that inherited a maternal translocation or inversion also demonstrated reduced expression of the growth suppressing imprinted gene, CDKN1C in Domain 2. In summary, our data demonstrate that translocations and inversions involving imprinted domain 2 on chromosome 11p15.5, alter regional DNA methylation patterns and imprinted gene expression in cis, suggesting that these epigenetic alterations are generated by an alteration in “chromatin context”. PMID:22079941

Extracellular microvesicle microRNAs in children with sickle cell anaemia with divergent clinical phenotypes.

PubMed

Khalyfa, Abdelnaby; Khalyfa, Ahamed A; Akbarpour, Mahzad; Connes, Phillippe; Romana, Marc; Lapping-Carr, Gabrielle; Zhang, Chunling; Andrade, Jorge; Gozal, David

2016-09-01

Sickle cell anaemia (SCA) is the most frequent genetic haemoglobinopathy, which exhibits a highly variable clinical course characterized by hyper-coagulable and pro-inflammatory states, as well as endothelial dysfunction. Extracellular microvesicles are released into biological fluids and play a role in modifying the functional phenotype of target cells. We hypothesized that potential differences in plasma-derived extracellular microvesicles (EV) function and cargo from SCA patients may underlie divergent clinical trajectories. Plasma EV from SCA patients with mild, intermediate and severe clinical disease course were isolated, and primary endothelial cell cultures were exposed. Endothelial cell activation, monocyte adhesion, barrier disruption and exosome cargo (microRNA microarrays) were assessed. EV disrupted the endothelial barrier and induced expression of adhesion molecules and monocyte adhesion in a SCA severity-dependent manner compared to healthy children. Microarray approaches identified a restricted signature of exosomal microRNAs that readily distinguished severe from mild SCA, as well as from healthy children. The microRNA candidates were further validated using quantitative real time polymerase chain reaction assays, and revealed putative gene targets. Circulating exosomal microRNAs may play important roles in predicting the clinical course of SCA, and in delineation of individually tailored, mechanistically-based clinical treatment approaches of SCA patients in the near future. © 2016 John Wiley & Sons Ltd.

Diffuse myogenin expression by immunohistochemistry is an independent marker of poor survival in pediatric rhabdomyosarcoma: a tissue microarray study of 71 primary tumors including correlation with molecular phenotype.

PubMed

Heerema-McKenney, Amy; Wijnaendts, Liliane C D; Pulliam, Joseph F; Lopez-Terrada, Dolores; McKenney, Jesse K; Zhu, Shirley; Montgomery, Kelli; Mitchell, Janet; Marinelli, Robert J; Hart, Augustinus A M; van de Rijn, Matt; Linn, Sabine C

2008-10-01

The pathologic classification of rhabdomyosarcoma (RMS) into embryonal or alveolar subtype is an important prognostic factor guiding the therapeutic protocol chosen for an individual patient. Unfortunately, this classification is not always straightforward, and the diagnostic criteria are controversial in a subset of cases. Ancillary studies are used to aid in the classification, but their potential use as independent prognostic factors is rarely studied. The aim of this study is to identify immunohistochemical markers of potential prognostic significance in pediatric RMS and to correlate their expression with PAX-3/FKHR and PAX-7/FKHR fusion status. A single tissue microarray containing 71 paraffin-embedded pediatric RMSs was immunostained with antibodies against p53, bcl-2, Ki-67, CD44, myogenin, and MyoD1. The tissue microarray and whole paraffin blocks were studied for PAX-3/FKHR and PAX-7/FKHR gene fusions by fluorescence in situ hybridization and reverse transcription-polymerase chain reaction. Clinical follow-up data were available for each patient. Immunohistochemical staining results and translocation status were correlated with recurrence-free interval (RFI) and overall survival (OS) using the Kaplan-Meier method, the log-rank test, and Cox proportional hazard regression. The minimum clinical follow-up interval was 24 months (median follow-up=57 mo). On univariable analysis, immunohistochemical expression of myogenin, bcl-2, and identification of a gene fusion were associated with decreased 5-year RFI and 10-year OS (myogenin RFI P=0.0028, OS P=0.0021; bcl-2 RFI P=0.037, OS P=0.032; gene fusion RFI P=0.0001, OS P=0.0058). After adjustment for Intergroup Rhabdomyosarcoma Study-TNM stage, tumor site, age, tumor histology, and translocation status by multivariable analysis, only myogenin retained an independent association with RFI (P=0.034) and OS (P=0.0069). In this retrospective analysis, diffuse immunohistochemical reactivity for myogenin in RMS correlates with decreased RFI and OS, independent of histologic subtype, translocation status, tumor site, or stage.

DNA sequencing and copy number variation analysis of MCHR2 in a cohort of Prader Willi like (PWL) patients.

PubMed

Geets, Ellen; Aerts, Evi; Verrijken, An; Van Hoorenbeeck, Kim; Verhulst, Stijn; Van Gaal, Luc; Van Hul, Wim

Prader Willi Syndrome (PWS) is a syndromic form of obesity caused by a chromosomal aberration on chromosome 15q11.2-q13. Patients with a comparable phenotype to PWS not carrying the 15q11.2-q13 defect are classified as Prader Willi like (PWL). In literature, PWL patients do frequently harbor deletions at 6q16, which led to the identification of the single-minded 1 (SIM1) gene as a possible cause for the presence of obesity in these patients. However, our previous work in a PWL cohort showed a rather limited involvement of SIM1 in the obesity phenotype. In this paper, we investigated the causal role of the melanin-concentrating hormone receptor 2 (MCHR2) gene in PWL patients, as most of the reported 6q16 deletions also encompass this gene and it is suggested to be active in the control of feeding behavior and energy metabolism. Copy number variation analysis of the MCHR2 genomic region followed by mutation analysis of MCHR2 was performed in a PWL cohort. Genome-wide microarray analysis of 109 patients with PWL did not show any gene harboring deletions on chromosome 6q16. Mutation analysis in 92 patients with PWL demonstrated three MCHR2 variants: p.T47A (c.139A>G), p.A76A (c.228T>C) and c.*16A>G. We identified a significantly higher prevalence of the c.228T>C C allele in our PWL cohort compared to previously published results and controls of the ExAC Database. Overall, our results are in line with some previously performed studies suggesting that MCHR2 is not a major contributor to human obesity and the PWL phenotype. Copyright © 2017 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Genome-Wide Survey on Genomic Variation, Expression Divergence, and Evolution in Two Contrasting Rice Genotypes under High Salinity Stress

PubMed Central

Jiang, Shu-Ye; Ma, Ali; Ramamoorthy, Rengasamy; Ramachandran, Srinivasan

2013-01-01

Expression profiling is one of the most important tools for dissecting biological functions of genes and the upregulation or downregulation of gene expression is sufficient for recreating phenotypic differences. Expression divergence of genes significantly contributes to phenotypic variations. However, little is known on the molecular basis of expression divergence and evolution among rice genotypes with contrasting phenotypes. In this study, we have implemented an integrative approach using bioinformatics and experimental analyses to provide insights into genomic variation, expression divergence, and evolution between salinity-sensitive rice variety Nipponbare and tolerant rice line Pokkali under normal and high salinity stress conditions. We have detected thousands of differentially expressed genes between these two genotypes and thousands of up- or downregulated genes under high salinity stress. Many genes were first detected with expression evidence using custom microarray analysis. Some gene families were preferentially regulated by high salinity stress and might play key roles in stress-responsive biological processes. Genomic variations in promoter regions resulted from single nucleotide polymorphisms, indels (1–10 bp of insertion/deletion), and structural variations significantly contributed to the expression divergence and regulation. Our data also showed that tandem and segmental duplication, CACTA and hAT elements played roles in the evolution of gene expression divergence and regulation between these two contrasting genotypes under normal or high salinity stress conditions. PMID:24121498

Hedgehog signaling regulates FOXA2 in esophageal embryogenesis and Barrett’s metaplasia

PubMed Central

Wang, David H.; Tiwari, Anjana; Kim, Monica E.; Clemons, Nicholas J.; Regmi, Nanda L.; Hodges, William A.; Berman, David M.; Montgomery, Elizabeth A.; Watkins, D. Neil; Zhang, Xi; Zhang, Qiuyang; Jie, Chunfa; Spechler, Stuart J.; Souza, Rhonda F.

2014-01-01

Metaplasia can result when injury reactivates latent developmental signaling pathways that determine cell phenotype. Barrett’s esophagus is a squamous-to-columnar epithelial metaplasia caused by reflux esophagitis. Hedgehog (Hh) signaling is active in columnar-lined, embryonic esophagus and inactive in squamous-lined, adult esophagus. We showed previously that Hh signaling is reactivated in Barrett’s metaplasia and overexpression of Sonic hedgehog (SHH) in mouse esophageal squamous epithelium leads to a columnar phenotype. Here, our objective was to identify Hh target genes involved in Barrett’s pathogenesis. By microarray analysis, we found that the transcription factor Foxa2 is more highly expressed in murine embryonic esophagus compared with postnatal esophagus. Conditional activation of Shh in mouse esophageal epithelium induced FOXA2, while FOXA2 expression was reduced in Shh knockout embryos, establishing Foxa2 as an esophageal Hh target gene. Evaluation of patient samples revealed FOXA2 expression in Barrett’s metaplasia, dysplasia, and adenocarcinoma but not in esophageal squamous epithelium or squamous cell carcinoma. In esophageal squamous cell lines, Hh signaling upregulated FOXA2, which induced expression of MUC2, an intestinal mucin found in Barrett’s esophagus, and the MUC2-processing protein AGR2. Together, these data indicate that Hh signaling induces expression of genes that determine an intestinal phenotype in esophageal squamous epithelial cells and may contribute to the development of Barrett’s metaplasia. PMID:25083987

Identifying biologically relevant putative mechanisms in a given phenotype comparison

PubMed Central

Hanoudi, Samer; Donato, Michele; Draghici, Sorin

2017-01-01

A major challenge in life science research is understanding the mechanism involved in a given phenotype. The ability to identify the correct mechanisms is needed in order to understand fundamental and very important phenomena such as mechanisms of disease, immune systems responses to various challenges, and mechanisms of drug action. The current data analysis methods focus on the identification of the differentially expressed (DE) genes using their fold change and/or p-values. Major shortcomings of this approach are that: i) it does not consider the interactions between genes; ii) its results are sensitive to the selection of the threshold(s) used, and iii) the set of genes produced by this approach is not always conducive to formulating mechanistic hypotheses. Here we present a method that can construct networks of genes that can be considered putative mechanisms. The putative mechanisms constructed by this approach are not limited to the set of DE genes, but also considers all known and relevant gene-gene interactions. We analyzed three real datasets for which both the causes of the phenotype, as well as the true mechanisms were known. We show that the method identified the correct mechanisms when applied on microarray datasets from mouse. We compared the results of our method with the results of the classical approach, showing that our method produces more meaningful biological insights. PMID:28486531

An unusual clinical severity of 16p11.2 deletion syndrome caused by unmasked recessive mutation of CLN3.

PubMed

Pebrel-Richard, Céline; Debost-Legrand, Anne; Eymard-Pierre, Eléonore; Greze, Victoria; Kemeny, Stéphan; Gay-Bellile, Mathilde; Gouas, Laetitia; Tchirkov, Andreï; Vago, Philippe; Goumy, Carole; Francannet, Christine

2014-03-01

With the introduction of array comparative genomic hybridization (aCGH) techniques in the diagnostic setting of patients with developmental delay and congenital malformations, many new microdeletion syndromes have been recognized. One of these recently recognized microdeletion syndromes is the 16p11.2 deletion syndrome, associated with variable clinical outcomes including developmental delay, autism spectrum disorder, epilepsy, and obesity, but also apparently normal phenotype. We report on a 16-year-old patient with developmental delay, exhibiting retinis pigmentosa with progressive visual failure from the age of 9 years, ataxia, and peripheral neuropathy. Chromosomal microarray analysis identified a 1.7-Mb 16p11.2 deletion encompassing the 593-kb common deletion (∼29.5 to ∼30.1 Mb; Hg18) and the 220-kb distal deletion (∼28.74 to ∼28.95 Mb; Hg18) that partially included the CLN3 gene. As the patient's clinical findings were different from usual 16p11.2 microdeletion phenotypes and showed some features reminiscent of juvenile neuronal ceroid-lipofuscinosis (JNCL, Batten disease, OMIM 204200), we suspected and confirmed a mutation of the remaining CLN3 allele. This case further illustrates that unmasking of hemizygous recessive mutations by chromosomal deletion represents one explanation for the phenotypic variability observed in chromosomal deletion disorders.

An unusual clinical severity of 16p11.2 deletion syndrome caused by unmasked recessive mutation of CLN3

PubMed Central

Pebrel-Richard, Céline; Debost-Legrand, Anne; Eymard-Pierre, Eléonore; Greze, Victoria; Kemeny, Stéphan; Gay-Bellile, Mathilde; Gouas, Laetitia; Tchirkov, Andreï; Vago, Philippe; Goumy, Carole; Francannet, Christine

2014-01-01

With the introduction of array comparative genomic hybridization (aCGH) techniques in the diagnostic setting of patients with developmental delay and congenital malformations, many new microdeletion syndromes have been recognized. One of these recently recognized microdeletion syndromes is the 16p11.2 deletion syndrome, associated with variable clinical outcomes including developmental delay, autism spectrum disorder, epilepsy, and obesity, but also apparently normal phenotype. We report on a 16-year-old patient with developmental delay, exhibiting retinis pigmentosa with progressive visual failure from the age of 9 years, ataxia, and peripheral neuropathy. Chromosomal microarray analysis identified a 1.7-Mb 16p11.2 deletion encompassing the 593-kb common deletion (∼29.5 to ∼30.1 Mb; Hg18) and the 220-kb distal deletion (∼28.74 to ∼28.95 Mb; Hg18) that partially included the CLN3 gene. As the patient's clinical findings were different from usual 16p11.2 microdeletion phenotypes and showed some features reminiscent of juvenile neuronal ceroid-lipofuscinosis (JNCL, Batten disease, OMIM 204200), we suspected and confirmed a mutation of the remaining CLN3 allele. This case further illustrates that unmasking of hemizygous recessive mutations by chromosomal deletion represents one explanation for the phenotypic variability observed in chromosomal deletion disorders. PMID:23860047

The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

PubMed Central

van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

2015-01-01

Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

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.

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

PubMed

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

2009-04-01

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

Support vector machine and principal component analysis for microarray data classification

NASA Astrophysics Data System (ADS)

Astuti, Widi; Adiwijaya

2018-03-01

Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

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…

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

Spot detection and image segmentation in DNA microarray data.

PubMed

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

2005-01-01

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

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.

Random forests-based differential analysis of gene sets for gene expression data.

PubMed

Hsueh, Huey-Miin; Zhou, Da-Wei; Tsai, Chen-An

2013-04-10

In DNA microarray studies, gene-set analysis (GSA) has become the focus of gene expression data analysis. GSA utilizes the gene expression profiles of functionally related gene sets in Gene Ontology (GO) categories or priori-defined biological classes to assess the significance of gene sets associated with clinical outcomes or phenotypes. Many statistical approaches have been proposed to determine whether such functionally related gene sets express differentially (enrichment and/or deletion) in variations of phenotypes. However, little attention has been given to the discriminatory power of gene sets and classification of patients. In this study, we propose a method of gene set analysis, in which gene sets are used to develop classifications of patients based on the Random Forest (RF) algorithm. The corresponding empirical p-value of an observed out-of-bag (OOB) error rate of the classifier is introduced to identify differentially expressed gene sets using an adequate resampling method. In addition, we discuss the impacts and correlations of genes within each gene set based on the measures of variable importance in the RF algorithm. Significant classifications are reported and visualized together with the underlying gene sets and their contribution to the phenotypes of interest. Numerical studies using both synthesized data and a series of publicly available gene expression data sets are conducted to evaluate the performance of the proposed methods. Compared with other hypothesis testing approaches, our proposed methods are reliable and successful in identifying enriched gene sets and in discovering the contributions of genes within a gene set. The classification results of identified gene sets can provide an valuable alternative to gene set testing to reveal the unknown, biologically relevant classes of samples or patients. In summary, our proposed method allows one to simultaneously assess the discriminatory ability of gene sets and the importance of genes for interpretation of data in complex biological systems. The classifications of biologically defined gene sets can reveal the underlying interactions of gene sets associated with the phenotypes, and provide an insightful complement to conventional gene set analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

Gene Expression Profiling of Benign and Malignant Pheochromocytoma

PubMed Central

BROUWERS, FREDERIEKE M.; ELKAHLOUN, ABDEL G.; MUNSON, PETER J.; EISENHOFER, GRAEME; BARB, JENNIFER; LINEHAN, W. MARSTON; LENDERS, JACQUES W.M.; DE KRIJGER, RONALD; MANNELLI, MASSIMO; UDELSMAN, ROBERT; OCAL, IDRIS T.; SHULKIN, BARRY L.; BORNSTEIN, STEFAN R.; BREZA, JAN; KSINANTOVA, LUCIA; PACAK, KAREL

2016-01-01

There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including metastases and primary tumors from which metastases developed. Other subgroups of tumors included those defined by tissue norepinephrine compared to epinephrine contents (i.e., noradrenergic versus adrenergic phenotypes), adrenal versus extra-adrenal locations, and presence of germline mutations of genes pre-disposing to the tumor. Correcting for the confounding influence of nora-drenergic versus adrenergic catecholamine phenotype by the analysis of variance revealed a larger and more accurate number of genes that discriminated benign from malignant pheochromocytomas than when the confounding influence of catecholamine phenotype was not considered. Seventy percent of these genes were underexpressed in malignant compared to benign tumors. Similarly, 89% of genes were underexpressed in malignant primary tumors compared to benign tumors, suggesting that malignant potential is largely characterized by a less-differentiated pattern of gene expression. The present database of differentially expressed genes provides a unique resource for mapping the pathways leading to malignancy and for establishing new targets for treatment and diagnostic and prognostic markers of malignant disease. The database may also be useful for examining mechanisms of tumorigenesis and genotype–phenotype relationships. Further progress on the basis of this database can be made from follow-up confirmatory studies, application of bioinformatics approaches for data mining and pathway analyses, testing in pheochromocytoma cell culture and animal model systems, and retrospective and prospective studies of diagnostic markers. PMID:17102123

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated With Acute Renal Allograft Rejection

PubMed Central

Shin, Heesun; Günther, Oliver; Hollander, Zsuzsanna; Wilson-McManus, Janet E.; Ng, Raymond T.; Balshaw, Robert; Keown, Paul A.; McMaster, Robert; McManus, Bruce M.; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature. PMID:24526836

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.

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 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

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

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...

Comparing transformation methods for DNA microarray data

PubMed Central

Thygesen, Helene H; Zwinderman, Aeilko H

2004-01-01

Background When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. Results We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. Conclusions The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method. PMID:15202953

Comparing transformation methods for DNA microarray data.

PubMed

Thygesen, Helene H; Zwinderman, Aeilko H

2004-06-17

When DNA microarray data are used for gene clustering, genotype/phenotype correlation studies, or tissue classification the signal intensities are usually transformed and normalized in several steps in order to improve comparability and signal/noise ratio. These steps may include subtraction of an estimated background signal, subtracting the reference signal, smoothing (to account for nonlinear measurement effects), and more. Different authors use different approaches, and it is generally not clear to users which method they should prefer. We used the ratio between biological variance and measurement variance (which is an F-like statistic) as a quality measure for transformation methods, and we demonstrate a method for maximizing that variance ratio on real data. We explore a number of transformations issues, including Box-Cox transformation, baseline shift, partial subtraction of the log-reference signal and smoothing. It appears that the optimal choice of parameters for the transformation methods depends on the data. Further, the behavior of the variance ratio, under the null hypothesis of zero biological variance, appears to depend on the choice of parameters. The use of replicates in microarray experiments is important. Adjustment for the null-hypothesis behavior of the variance ratio is critical to the selection of transformation method.

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

NASA Astrophysics Data System (ADS)

Bogdanov, Valery L.; Boyce-Jacino, Michael

1999-05-01

Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.

A Novel Method to Screen for Dominant Negative ATM Mutations in Familial Breast Cancer

DTIC Science & Technology

2005-04-01

carry dominant negative mutation in ATM due to natural variation amongst LCLs. Microarrays have been performed to determine differences in gene expression... genes that are altered in their expression in ATMmutation carriers. The validation of this data in carriers of different ATM mutation indicated that the...heterozygous carriers of T727 1 G mutation display a gene expression phenotype that appears identical to carriers of protein truncating mutations in

Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

NASA Astrophysics Data System (ADS)

Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

NHR-23 dependent collagen and hedgehog-related genes required for molting

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

Kouns, Nathaniel A.; Nakielna, Johana; Behensky, Frantisek

2011-10-07

Highlights: {yields} NHR-23 is a critical regulator of nematode development and molting. {yields} The manuscript characterizes the loss-of-function phenotype of an nhr-23 mutant. {yields} Whole genome expression analysis identifies new potential targets of NHR-23. {yields} Hedgehog-related genes are identified as NHR-23 dependent genes. {yields} New link between sterol mediated signaling and regulation by NHR-23 is found. -- Abstract: NHR-23, a conserved member of the nuclear receptor family of transcription factors, is required for normal development in Caenorhabditis elegans where it plays a critical role in growth and molting. In a search for NHR-23 dependent genes, we performed whole genome comparativemore » expression microarrays on both control and nhr-23 inhibited synchronized larvae. Genes that decreased in response to nhr-23 RNAi included several collagen genes. Unexpectedly, several hedgehog-related genes were also down-regulated after nhr-23 RNAi. A homozygous nhr-23 deletion allele was used to confirm the RNAi knockdown phenotypes and the changes in gene expression. Our results indicate that NHR-23 is a critical co-regulator of functionally linked genes involved in growth and molting and reveal evolutionary parallels among the ecdysozoa.« less

Prediction of Human Disease Genes by Human-Mouse Conserved Coexpression Analysis

PubMed Central

Grassi, Elena; Damasco, Christian; Silengo, Lorenzo; Oti, Martin; Provero, Paolo; Di Cunto, Ferdinando

2008-01-01

Background Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates. Methodology/Principal Findings We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases. Conclusion Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes. PMID:18369433

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.

Implementation of GenePattern within the Stanford Microarray Database.

PubMed

Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

2009-01-01

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

Phenotypic and genomic survey on organic acid utilization profile of Pseudomonas mendocina strain S5.2, a vineyard soil isolate.

PubMed

Chong, Teik Min; Chen, Jian-Woon; See-Too, Wah-Seng; Yu, Choo-Yee; Ang, Geik-Yong; Lim, Yan Lue; Yin, Wai-Fong; Grandclément, Catherine; Faure, Denis; Dessaux, Yves; Chan, Kok-Gan

2017-12-01

Root exudates are chemical compounds that are released from living plant roots and provide significant energy, carbon, nitrogen and phosphorus sources for microbes inhabiting the rhizosphere. The exudates shape the microflora associated with the plant, as well as influences the plant health and productivity. Therefore, a better understanding of the trophic link that is established between the plant and the associated bacteria is necessary. In this study, a comprehensive survey on the utilization of grapevine and rootstock related organic acids were conducted on a vineyard soil isolate which is Pseudomonas mendocina strain S5.2. Phenotype microarray analysis has demonstrated that this strain can utilize several organic acids including lactic acid, succinic acid, malic acid, citric acid and fumaric acid as sole growth substrates. Complete genome analysis using single molecule real-time technology revealed that the genome consists of a 5,120,146 bp circular chromosome and a 252,328 bp megaplasmid. A series of genetic determinants associated with the carbon utilization signature of the strain were subsequently identified in the chromosome. Of note, the coexistence of genes encoding several iron-sulfur cluster independent isoenzymes in the genome indicated the importance of these enzymes in the events of iron deficiency. Synteny and comparative analysis have also unraveled the unique features of D-lactate dehydrogenase of strain S5.2 in the study. Collective information of this work has provided insights on the metabolic role of this strain in vineyard soil rhizosphere.

The laboratory-clinician team: a professional call to action to improve communication and collaboration for optimal patient care in chromosomal microarray testing.

PubMed

Wain, Karen E; Riggs, Erin; Hanson, Karen; Savage, Melissa; Riethmaier, Darlene; Muirhead, Andrea; Mitchell, Elyse; Packard, Bethanny Smith; Faucett, W Andrew

2012-10-01

The International Standards for Cytogenomic Arrays (ISCA) Consortium is a worldwide collaborative effort dedicated to optimizing patient care by improving the quality of chromosomal microarray testing. The primary effort of the ISCA Consortium has been the development of a database of copy number variants (CNVs) identified during the course of clinical microarray testing. This database is a powerful resource for clinicians, laboratories, and researchers, and can be utilized for a variety of applications, such as facilitating standardized interpretations of certain CNVs across laboratories or providing phenotypic information for counseling purposes when published data is sparse. A recognized limitation to the clinical utility of this database, however, is the quality of clinical information available for each patient. Clinical genetic counselors are uniquely suited to facilitate the communication of this information to the laboratory by virtue of their existing clinical responsibilities, case management skills, and appreciation of the evolving nature of scientific knowledge. We intend to highlight the critical role that genetic counselors play in ensuring optimal patient care through contributing to the clinical utility of the ISCA Consortium's database, as well as the quality of individual patient microarray reports provided by contributing laboratories. Current tools, paper and electronic forms, created to maximize this collaboration are shared. In addition to making a professional commitment to providing complete clinical information, genetic counselors are invited to become ISCA members and to become involved in the discussions and initiatives within the Consortium.

Morphologic, phenotypic, and transcriptomic characterization of classically and alternatively activated canine blood-derived macrophages in vitro

PubMed Central

Heinrich, Franziska; Lehmbecker, Annika; Raddatz, Barbara B.; Kegler, Kristel; Tipold, Andrea; Stein, Veronika M.; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner

2017-01-01

Macrophages are a heterogeneous cell population playing a pivotal role in tissue homeostasis and inflammation, and their phenotype strongly depends on the micromilieu. Despite its increasing importance as a translational animal model for human diseases, there is a considerable gap of knowledge with respect to macrophage polarization in dogs. The present study comprehensively investigated the morphologic, phenotypic, and transcriptomic characteristics of unstimulated (M0), M1- (GM-CSF, LPS, IFNγ-stimulated) and M2- (M-CSF, IL-4-stimulated)-polarized canine blood-derived macrophages in vitro. Scanning electron microscopy revealed distinct morphologies of polarized macrophages with formation of multinucleated cells in M2-macrophages, while immunofluorescence employing literature-based prototype-antibodies against CD16, CD32, iNOS, MHC class II (M1-markers), CD163, CD206, and arginase-1 (M2-markers) demonstrated that only CD206 was able to discriminate M2-macrophages from both other phenotypes, highlighting this molecule as a promising marker for canine M2-macrophages. Global microarray analysis revealed profound changes in the transcriptome of polarized canine macrophages. Functional analysis pointed out that M1-polarization was associated with biological processes such as “respiratory burst”, whereas M2-polarization was associated with processes such as “mitosis”. Literature-based marker gene selection revealed only minor overlaps in the gene sets of the dog compared to prototype markers of murine and human macrophages. Biomarker selection using supervised clustering suggested latexin (LXN) and membrane-spanning 4-domains, subfamily A, member 2 (MS4A2) to be the most powerful predicting biomarkers for canine M1- and M2-macrophages, respectively. Immunofluorescence for both markers demonstrated expression of both proteins by macrophages in vitro but failed to reveal differences between canine M1 and M2-macrophages. The present study provides a solid basis for future studies upon the role of macrophage polarization in spontaneous diseases of the dog, a species that has emerging importance for translational research. PMID:28817687

Up-regulation of lymphocyte antigen 6 complex expression in side-population cells derived from a human trophoblast cell line HTR-8/SVneo.

PubMed

Inagaki, Tetsunori; Kusunoki, Soshi; Tabu, Kouichi; Okabe, Hitomi; Yamada, Izumi; Taga, Tetsuya; Matsumoto, Akemi; Makino, Shintaro; Takeda, Satoru; Kato, Kiyoko

2016-01-01

The continual proliferation and differentiation of trophoblasts are critical for the maintenance of pregnancy. It is well known that the tissue stem cells are associated with the development of tissues and pathologies. It has been demonstrated that side-population (SP) cells identified by fluorescence-activated cell sorting (FACS) are enriched with stem cells. The SP cells in HTR-8/SVneo cells derived from human primary trophoblast cells were isolated by FACS. HTR-8/SVneo-SP cell cultures generated both SP and non-SP (NSP) subpopulations. In contrast, NSP cell cultures produced NSP cells and failed to produce SP cells. These SP cells showed self-renewal capability by serial colony-forming assay. Microarray expression analysis using a set of HTR-8/SVneo-SP and -NSP cells revealed that SP cells overexpressed several stemness genes including caudal type homeobox2 (CDX2) and bone morphogenic proteins (BMPs), and lymphocyte antigen 6 complex locus D (LY6D) gene was the most highly up-regulated in HTR-8/SVneo-SP cells. LY6D gene reduced its expression in the course of a 7-day cultivation in differentiation medium. SP cells tended to reduce its fraction by treatment of LY6D siRNA indicating that LY6D had potential to maintain cell proliferation of HTR-8/SVneo-SP cells. On ontology analysis, epithelial-mesenchymal transition (EMT) pathway was involved in the up-regulated genes on microarray analysis. HTR-SVneo-SP cells showed enhanced migration. This is the first report that LY6D was important for the maintenance of HTR-8/SVneo-SP cells. EMT was associated with the phenotype of these SP cells.

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

PubMed Central

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

2009-01-01

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

Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood.

PubMed

Aspler, Anne L; Bolshin, Carly; Vernon, Suzanne D; Broderick, Gordon

2008-09-26

Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS) however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood. Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention) and unsupervised latent cluster analysis (LCA). Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in co-expression identified from topological evaluation of linear correlation networks. Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p = 0.01) due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p < 0.05, patterns of co-expression in each group differed markedly. Significant co-expression of CD14+ monocyte with CD16+ neutrophil (p = 0.01) and CD19+ B cell sets (p = 0.00) characterized CFS and fatigue phenotype groups. Also in CFS was a significant negative correlation between CD8+ and both CD19+ up-regulated (p = 0.02) and NK gene sets (p = 0.08). These patterns were absent in controls. Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

The Regulation of Non-Coding RNA Expression in the Liver of Mice Fed DDC

PubMed Central

Oliva, Joan; Bardag-Gorce, Fawzia; French, Barbara A; Li, Jun; French, Samuel W

2010-01-01

Mallory-Denk bodies (MDBs) are found in the liver of patients with alcoholic and chronic nonalcoholic liver disease, and hepatocellular carcinoma (HCC). Diethyl 1,4-dihydro-2,4,6,-trimethyl-3,5-pyridinedicarboxylate (DDC) is used as a model to induce the formation of MDBs in mouse liver. Previous studies in this laboratory showed that DDC induced epigenetic modifications in DNA and histones. The combination of these modifications changes the phenotype of the MDB forming hepatocytes, as indicated by the marker FAT10. These epigenetic modifications are partially prevented by adding to the diet S-adenosylmethionine (SAMe) or betaine, both methyl donors. The expression of three imprinted ncRNA genes was found to change in MDB forming hepatocytes, which is the subject of this report. NcRNA expression was quantitated by Real-Time PCR and RNA FISH in liver sections. Microarray analysis showed that the expression of three ncRNAs was regulated by DDC: up regulation of H19, antisense Igf2r (AIR), and down regulation of GTL2 (also called MEG3). S-adenosylmethionine (SAMe) feeding prevented these changes. Betaine, another methyl group donor, prevented only H19 and AIR up regulation induced by DDC, on microarrays. The results of the SAMe and betaine groups were confirmed by Real-Time PCR, except for AIR expression. After 1 month of drug withdrawal, the expression of the three ncRNAs tended toward control levels of expression. Liver tumors that developed also showed up regulation of H19 and AIR. The RNA FISH approach showed that the MDB forming cells’ phenotype changed the level of expression of AIR, H19 and GTL2, compared to the surrounding cells. Furthermore, over expression of H19 and AIR was demonstrated in tumors formed in mice withdrawn for 9 months. The disregulation of ncRNA in MDB forming liver cells has been observed for the first time in drug primed mice associated with liver preneoplastic foci and tumors. PMID:19362547

Reciprocal transcriptional regulation of metabolic and signaling pathways correlates with disease severity in heart failure.

PubMed

Barth, Andreas S; Kumordzie, Ami; Frangakis, Constantine; Margulies, Kenneth B; Cappola, Thomas P; Tomaselli, Gordon F

2011-10-01

Systolic heart failure (HF) is a complex systemic syndrome that can result from a wide variety of clinical conditions and gene mutations. Despite phenotypic similarities, characterized by ventricular dilatation and reduced contractility, the extent of common and divergent gene expression between different forms of HF remains a matter of intense debate. Using a meta-analysis of 28 experimental (mouse, rat, dog) and human HF microarray studies, we demonstrate that gene expression changes are characterized by a coordinated and reciprocal regulation of major metabolic and signaling pathways. In response to a wide variety of stressors in animal models of HF, including ischemia, pressure overload, tachypacing, chronic isoproterenol infusion, Chagas disease, and transgenic mouse models, major metabolic pathways are invariably downregulated, whereas cell signaling pathways are upregulated. In contrast to this uniform transcriptional pattern that recapitulates a fetal gene expression program in experimental animal models of HF, human HF microarray studies displayed a greater heterogeneity, with some studies even showing upregulation of metabolic and downregulation of signaling pathways in end-stage human hearts. These discrepant results between animal and human studies are due to a number of factors, prominently cardiac disease and variable exposure to cold cardioplegic solution in nonfailing human samples, which can downregulate transcripts involved in oxidative phosphorylation (OXPHOS), thus mimicking gene expression patterns observed in failing samples. Additionally, β-blockers and ACE inhibitor use in end-stage human HF was associated with higher levels of myocardial OXPHOS transcripts, thus partially reversing the fetal gene expression pattern. In human failing samples, downregulation of metabolism was associated with hemodynamic markers of disease severity. Irrespective of the etiology, gene expression in failing myocardium is characterized by downregulation of metabolic transcripts and concomitant upregulation of cell signaling pathways. Gene expression changes along this metabolic-signaling axis in mammalian myocardium are a consistent feature in the heterogeneous transcriptional response observed in phenotypically similar models of HF.

The regulation of non-coding RNA expression in the liver of mice fed DDC.

PubMed

Oliva, Joan; Bardag-Gorce, Fawzia; French, Barbara A; Li, Jun; French, Samuel W

2009-08-01

Mallory-Denk bodies (MDBs) are found in the liver of patients with alcoholic and chronic nonalcoholic liver disease, and hepatocellular carcinoma (HCC). Diethyl 1,4-dihydro-2,4,6,-trimethyl-3,5-pyridinedicarboxylate (DDC) is used as a model to induce the formation of MDBs in mouse liver. Previous studies in this laboratory showed that DDC induced epigenetic modifications in DNA and histones. The combination of these modifications changes the phenotype of the MDB forming hepatocytes, as indicated by the marker FAT10. These epigenetic modifications are partially prevented by adding to the diet S-adenosylmethionine (SAMe) or betaine, both methyl donors. The expression of three imprinted ncRNA genes was found to change in MDB forming hepatocytes, which is the subject of this report. NcRNA expression was quantitated by real-time PCR and RNA FISH in liver sections. Microarray analysis showed that the expression of three ncRNAs was regulated by DDC: up regulation of H19, antisense Igf2r (AIR), and down regulation of GTL2 (also called MEG3). S-adenosylmethionine (SAMe) feeding prevented these changes. Betaine, another methyl group donor, prevented only H19 and AIR up regulation induced by DDC, on microarrays. The results of the SAMe and betaine groups were confirmed by real-time PCR, except for AIR expression. After 1 month of drug withdrawal, the expression of the three ncRNAs tended toward control levels of expression. Liver tumors that developed also showed up regulation of H19 and AIR. The RNA FISH approach showed that the MDB forming cells' phenotype changed the level of expression of AIR, H19 and GTL2, compared to the surrounding cells. Furthermore, over expression of H19 and AIR was demonstrated in tumors formed in mice withdrawn for 9 months. The dysregulation of ncRNA in MDB forming liver cells has been observed for the first time in drug-primed mice associated with liver preneoplastic foci and tumors.

Behaviorally activated mRNA expression profiles produce signatures of learning and enhanced inhibition in aged rats with preserved memory.

PubMed

Haberman, Rebecca P; Colantuoni, Carlo; Koh, Ming Teng; Gallagher, Michela

2013-01-01

Aging is often associated with cognitive decline, but many elderly individuals maintain a high level of function throughout life. Here we studied outbred rats, which also exhibit individual differences across a spectrum of outcomes that includes both preserved and impaired spatial memory. Previous work in this model identified the CA3 subfield of the hippocampus as a region critically affected by age and integral to differing cognitive outcomes. Earlier microarray profiling revealed distinct gene expression profiles in the CA3 region, under basal conditions, for aged rats with intact memory and those with impairment. Because prominent age-related deficits within the CA3 occur during neural encoding of new information, here we used microarray analysis to gain a broad perspective of the aged CA3 transcriptome under activated conditions. Behaviorally-induced CA3 expression profiles differentiated aged rats with intact memory from those with impaired memory. In the activated profile, we observed substantial numbers of genes (greater than 1000) exhibiting increased expression in aged unimpaired rats relative to aged impaired, including many involved in synaptic plasticity and memory mechanisms. This unimpaired aged profile also overlapped significantly with a learning induced gene profile previously acquired in young adults. Alongside the increased transcripts common to both young learning and aged rats with preserved memory, many transcripts behaviorally-activated in the current study had previously been identified as repressed in the aged unimpaired phenotype in basal expression. A further distinct feature of the activated profile of aged rats with intact memory is the increased expression of an ensemble of genes involved in inhibitory synapse function, which could control the phenotype of neural hyperexcitability found in the CA3 region of aged impaired rats. These data support the conclusion that aged subjects with preserved memory recruit adaptive mechanisms to retain tight control over excitability under both basal and activated conditions.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

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

PubMed Central

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

2009-01-01

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

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

PubMed

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

2009-09-04

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

Evolution of the BBAA Component of Bread Wheat during Its History at the Allohexaploid Level[C][W][OPEN

PubMed Central

Zhang, Huakun; Zhu, Bo; Qi, Bao; Gou, Xiaowan; Dong, Yuzhu; Xu, Chunming; Zhang, Bangjiao; Huang, Wei; Liu, Chang; Wang, Xutong; Yang, Chunwu; Zhou, Hao; Kashkush, Khalil; Feldman, Moshe; Wendel, Jonathan F.; Liu, Bao

2014-01-01

Subgenome integrity in bread wheat (Triticum aestivum; BBAADD) makes possible the extraction of its BBAA component to restitute a novel plant type. The availability of such a ploidy-reversed wheat (extracted tetraploid wheat [ETW]) provides a unique opportunity to address whether and to what extent the BBAA component of bread wheat has been modified in phenotype, karyotype, and gene expression during its evolutionary history at the allohexaploid level. We report here that ETW was anomalous in multiple phenotypic traits but maintained a stable karyotype. Microarray-based transcriptome profiling identified a large number of differentially expressed genes between ETW and natural tetraploid wheat (Triticum turgidum), and the ETW-downregulated genes were enriched for distinct Gene Ontology categories. Quantitative RT-PCR analysis showed that gene expression differences between ETW and a set of diverse durum wheat (T. turgidum subsp durum) cultivars were distinct from those characterizing tetraploid cultivars per se. Pyrosequencing revealed that the expression alterations may occur to either only one or both of the B and A homoeolog transcripts in ETW. A majority of the genes showed additive expression in a resynthesized allohexaploid wheat. Analysis of a synthetic allohexaploid wheat and diverse bread wheat cultivars revealed the rapid occurrence of expression changes to the BBAA subgenomes subsequent to allohexaploidization and their evolutionary persistence. PMID:24989045

Differentiation and activation of equine monocyte-derived dendritic cells are not correlated with CD206 or CD83 expression

PubMed Central

Moyo, Nathifa A; Marchi, Emanuele; Steinbach, Falko

2013-01-01

Dendritic cells (DC) are the main immune mediators inducing primary immune responses. DC generated from monocytes (MoDC) are a model system to study the biology of DC in vitro, as they represent inflammatory DC in vivo. Previous studies on the generation of MoDC in horses indicated that there was no distinct difference between immature and mature DC and that the expression profile was distinctly different from humans, where CD206 is expressed on immature MoDC whereas CD83 is expressed on mature MoDC. Here we describe the kinetics of equine MoDC differentiation and activation, analysing both phenotypic and functional characteristics. Blood monocytes were first differentiated with equine granulocyte–macrophage colony-stimulating factor and interleukin-4 generating immature DC (iMoDC). These cells were further activated with a cocktail of cytokines including interferon-γ) but not CD40 ligand to obtain mature DC (mMoDC). To determine the expression of a broad range of markers for which no monoclonal antibodies were available to analyse the protein expression, microarray and quantitative PCR analysis were performed to carry out gene expression analysis. This study demonstrates that equine iMoDC and mMoDC can be distinguished both phenotypically and functionally but the expression pattern of some markers including CD206 and CD83 is dissimilar to the human system. PMID:23461413

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

TOXICOGENOMIC ANALYSIS INCORPORATING OPERON-TRANSCRIPTIONAL COUPLING AND TOXICANT CONCENTRATRION-EXPRESSION RESPONSE: Analysis of MX-Treated Salmonella

EPA Science Inventory

What is the study? This study is the first to use microarray analysis in the Ames strains of Salmonella. The microarray chips were custom-designed for this study and are not commercially available, and we evaluated the well-studied drinking water mutagen, MX. Because much inform...

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...

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.

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.

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

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.

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.

Serum response factor: positive and negative regulation of an epithelial gene expression network in the destrin mutant cornea

PubMed Central

Kawakami-Schulz, Sharolyn V.; Verdoni, Angela M.; Sattler, Shannon G.; Jessen, Erik; Kao, Winston W.-Y.; Ikeda, Akihiro

2014-01-01

Increased angiogenesis, inflammation, and proliferation are hallmarks of diseased tissues, and in vivo models of these disease phenotypes can provide insight into disease pathology. Dstncorn1 mice, deficient for the actin depolymerizing factor destrin (DSTN), display an increase of serum response factor (SRF) that results in epithelial hyperproliferation, inflammation, and neovascularization in the cornea. Previous work demonstrated that conditional ablation of Srf from the corneal epithelium of Dstncorn1 mice returns the cornea to a wild-type (WT) like state. This result implicated SRF as a major regulator of genes that contributes to abnormal phenotypes in Dstncorn1 cornea. The purpose of this study is to identify gene networks that are affected by increased expression of Srf in the Dstncorn1 cornea. Microarray analysis led to characterization of gene expression changes that occur when conditional knockout of Srf rescues mutant phenotypes in the cornea of Dstncorn1 mice. Comparison of gene expression values from WT, Dstncorn1 mutant, and Dstncorn1 rescued cornea identified >400 differentially expressed genes that are downstream from SRF. Srf ablation had a significant effect on genes associated with epithelial cell-cell junctions and regulation of actin dynamics. The majority of genes affected by SRF are downregulated in the Dstncorn1 mutant cornea, suggesting that increased SRF negatively affects transcription of SRF gene targets. ChIP-seq analysis on Dstncorn1 mutant and WT tissue revealed that, despite being present in higher abundance, SRF binding is significantly decreased in the Dstncorn1 mutant cornea. This study uses a unique model combining genetic and genomic approaches to identify genes that are regulated by SRF. These findings expand current understanding of the role of SRF in both normal and abnormal tissue homeostasis. PMID:24550211

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

PubMed Central

SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

2016-01-01

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

Mesenchymal change and drug resistance in neuroblastoma.

PubMed

Naiditch, Jessica A; Jie, Chunfa; Lautz, Timothy B; Yu, Songtao; Clark, Sandra; Voronov, Dimitry; Chu, Fei; Madonna, Mary Beth

2015-01-01

Metastatic initiation has many phenotypic similarities to epithelial-to-mesenchymal transition, including loss of cell-cell adhesion, increased invasiveness, and increased cell mobility. We have previously demonstrated that drug resistance is associated with a metastatic phenotype in neuroblastoma (NB). The purpose of this project was to determine if the development of doxorubicin resistance is associated with characteristics of mesenchymal change in human NB cells. Total RNA was isolated from wild type (WT) and doxorubicin-resistant (DoxR) human NB cell lines (SK-N-SH and SK-N-BE(2)C) and analyzed using the Illumina Human HT-12 version 4 Expression BeadChip. Differentially expressed genes (DEGs) were identified. Volcano plots and heat maps were generated. Genes of interest with a fold change in expression >1.5 and an adjusted P < 0.1 were analyzed. Immunofluorescence (IF) and Western blot analysis confirmed microarray results of interest. Matrigel invasion assay and migration wounding assays were performed. Volcano plots and heat maps visually demonstrated a similar pattern of DEGs in the SK-N-SH and SK-N-BE(2)C DoxR cell lines relative to their parental WT lines. Venn diagramming revealed 1594 DEGs common to both DoxR cell lines relative to their parental cell lines. Network analysis pointed to several significantly upregulated epithelial-to-mesenchymal transition pathways, through TGF-beta pathways via RhoA, PI3K, and ILK and via SMADs, as well as via notch signaling pathways. DoxR cell lines displayed a more invasive phenotype than respective WT cell lines. Human SK-N-SH and SK-N-BE(2)C NB cells display characteristics of mesenchymal change via multiple pathways in the transition to a drug-resistant state. Copyright © 2015 Elsevier Inc. All rights reserved.

Molecular and clinical characterization of two patients with Prader-Willi syndrome and atypical deletions of proximal chromosome 15q.

PubMed

Calounova, Gabriela; Hedvicakova, Petra; Silhanova, Eva; Kreckova, Gabriela; Sedlacek, Zdenek

2008-08-01

Prader-Willi syndrome (PWS) is caused by the disturbed expression of genes from the imprinted region of 15q11-q13, but the specific contributions of individual genes remain unknown. Most paternal PWS deletions are bracketed by recurrent breakpoints BP1 or BP2 and BP3. Atypical deletions are very rare. In the present work, we describe the molecular analysis of two patients with atypical deletions using microsatellite analysis, methylation-specific MLPA, and microarray CGH. A deletion of about 2 Mb in Patient 1 started at BP2 and ended in the middle of the typically deleted region within the UBE3A gene. The deletion in Patient 2 started 1.3 Mb distal from BP2 within the C15ORF2 gene, extended over 9.5 Mb, and ended within the AVEN gene in proximal 15q14. In Patient 1 both deletion breakpoints involved repetitive regions, which precluded cloning of the junction and pointed to non-allelic homologous recombination as a possible mechanism of this rearrangement. The breakpoints in Patient 2 were sequenced, and their structure suggested non-homologous end joining as the most likely cause of this deletion. The phenotype of both patients did not depart significantly from the typical clinical picture of PWS, although some symptoms in Patient 2 were also reminiscent of the phenotype of individuals with the recently described 15q13.3 microdeletion syndrome. Our findings support previous observations of relatively mild phenotypic effects resulting from deletions that extend distally from the PWS region and observations of the modest effects of different types of genetic defects on the spectrum and severity of symptoms in PWS. Copyright 2008 Wiley-Liss, Inc.

Polyadenylation state microarray (PASTA) analysis.

PubMed

Beilharz, Traude H; Preiss, Thomas

2011-01-01

Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer.

PubMed

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando; Treviño, Victor

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures.

Radiogenomics analysis identifies correlations of digital mammography with clinical molecular signatures in breast cancer

PubMed Central

Tamez-Peña, Jose-Gerardo; Rodriguez-Rojas, Juan-Andrés; Gomez-Rueda, Hugo; Celaya-Padilla, Jose-Maria; Rivera-Prieto, Roxana-Alicia; Palacios-Corona, Rebeca; Garza-Montemayor, Margarita; Cardona-Huerta, Servando

2018-01-01

In breast cancer, well-known gene expression subtypes have been related to a specific clinical outcome. However, their impact on the breast tissue phenotype has been poorly studied. Here, we investigate the association of imaging data of tumors to gene expression signatures from 71 patients with breast cancer that underwent pre-treatment digital mammograms and tumor biopsies. From digital mammograms, a semi-automated radiogenomics analysis generated 1,078 features describing the shape, signal distribution, and texture of tumors along their contralateral image used as control. From tumor biopsy, we estimated the OncotypeDX and PAM50 recurrence scores using gene expression microarrays. Then, we used multivariate analysis under stringent cross-validation to train models predicting recurrence scores. Few univariate features reached Spearman correlation coefficients above 0.4. Nevertheless, multivariate analysis yielded significantly correlated models for both signatures (correlation of OncotypeDX = 0.49 ± 0.07 and PAM50 = 0.32 ± 0.10 in stringent cross-validation and OncotypeDX = 0.83 and PAM50 = 0.78 for a unique model). Equivalent models trained from the unaffected contralateral breast were not correlated suggesting that the image signatures were tumor-specific and that overfitting was not a considerable issue. We also noted that models were improved by combining clinical information (triple negative status and progesterone receptor). The models used mostly wavelets and fractal features suggesting their importance to capture tumor information. Our results suggest that molecular-based recurrence risk and breast cancer subtypes have observable radiographic phenotypes. To our knowledge, this is the first study associating mammographic information to gene expression recurrence signatures. PMID:29596496

Metabolic potential of lithifying cyanobacteria-dominated thrombolitic mats.

PubMed

Mobberley, Jennifer M; Khodadad, Christina L M; Foster, Jamie S

2013-11-01

Thrombolites are unlaminated carbonate deposits formed by the metabolic activities of microbial mats and can serve as potential models for understanding the molecular mechanisms underlying the formation of lithifying communities. To assess the metabolic complexity of these ecosystems, high throughput DNA sequencing of a thrombolitic mat metagenome was coupled with phenotypic microarray analysis. Functional protein analysis of the thrombolite community metagenome delineated several of the major metabolic pathways that influence carbonate mineralization including cyanobacterial photosynthesis, sulfate reduction, sulfide oxidation, and aerobic heterotrophy. Spatial profiling of metabolite utilization within the thrombolite-forming microbial mats suggested that the top 5 mm contained a more metabolically diverse and active community than the deeper within the mat. This study provides evidence that despite the lack of mineral layering within the clotted thrombolite structure there is a vertical gradient of metabolic activity within the thrombolitic mat community. This metagenomic profiling also serves as a foundation for examining the active role individual functional groups of microbes play in coordinating metabolisms that lead to mineralization.

Differential global gene expression in red and white skeletal muscle

NASA Technical Reports Server (NTRS)

Campbell, W. G.; Gordon, S. E.; Carlson, C. J.; Pattison, J. S.; Hamilton, M. T.; Booth, F. W.

2001-01-01

The differences in gene expression among the fiber types of skeletal muscle have long fascinated scientists, but for the most part, previous experiments have only reported differences of one or two genes at a time. The evolving technology of global mRNA expression analysis was employed to determine the potential differential expression of approximately 3,000 mRNAs between the white quad (white muscle) and the red soleus muscle (mixed red muscle) of female ICR mice (30-35 g). Microarray analysis identified 49 mRNA sequences that were differentially expressed between white and mixed red skeletal muscle, including newly identified differential expressions between muscle types. For example, the current findings increase the number of known, differentially expressed mRNAs for transcription factors/coregulators by nine and signaling proteins by three. The expanding knowledge of the diversity of mRNA expression between white and mixed red muscle suggests that there could be quite a complex regulation of phenotype between muscles of different fiber types.

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

PubMed

Robinson, Mark D; McCarthy, Davis J; Smyth, Gordon K

2010-01-01

It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).

A role for PDGF-C/PDGFRα signaling in the formation of the meningeal basement membranes surrounding the cerebral cortex

PubMed Central

Andrae, Johanna; Gouveia, Leonor; Gallini, Radiosa; He, Liqun; Fredriksson, Linda; Nilsson, Ingrid; Johansson, Bengt R.; Eriksson, Ulf; Betsholtz, Christer

2016-01-01

ABSTRACT Platelet-derived growth factor-C (PDGF-C) is one of three known ligands for the tyrosine kinase receptor PDGFRα. Analysis of Pdgfc null mice has demonstrated roles for PDGF-C in palate closure and the formation of cerebral ventricles, but redundancy with other PDGFRα ligands might obscure additional functions. In search of further developmental roles for PDGF-C, we generated mice that were double mutants for Pdgfc−/− and PdgfraGFP/+. These mice display a range of severe phenotypes including spina bifida, lung emphysema, abnormal meninges and neuronal over-migration in the cerebral cortex. We focused our analysis on the central nervous system (CNS), where PDGF-C was identified as a critical factor for the formation of meninges and assembly of the glia limitans basement membrane. We also present expression data on Pdgfa, Pdgfc and Pdgfra in the cerebral cortex and microarray data on cerebral meninges. PMID:26988758

The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

PubMed

Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

2015-01-01

Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

T Cell Dynamic Activation and Functional Analysis in Nanoliter Droplet Microarray.

PubMed

Sarkar, Saheli; Motwani, Vinny; Sabhachandani, Pooja; Cohen, Noa; Konry, Tania

2015-06-01

Characterization of the heterogeneity in immune reactions requires assessing dynamic single cell responses as well as interactions between the various immune cell subsets. Maturation and activation of effector cells is regulated by cell contact-dependent and soluble factor-mediated paracrine signalling. Currently there are few methods available that allow dynamic investigation of both processes simultaneously without physically constraining non-adherent cells and eliminating crosstalk from neighboring cell pairs. We describe here a microfluidic droplet microarray platform that permits rapid functional analysis of single cell responses and co-encapsulation of heterotypic cell pairs, thereby allowing us to evaluate the dynamic activation state of primary T cells. The microfluidic droplet platform enables generation and docking of monodisperse nanoliter volume (0.523 nl) droplets, with the capacity of monitoring a thousand droplets per experiment. Single human T cells were encapsulated in droplets and stimulated on-chip with the calcium ionophore ionomycin. T cells were also co-encapsulated with dendritic cells activated by ovalbumin peptide, followed by dynamic calcium signal monitoring. Ionomycin-stimulated cells depicted fluctuation in calcium signalling compared to control. Both cell populations demonstrated marked heterogeneity in responses. Calcium signalling was observed in T cells immediately following contact with DCs, suggesting an early activation signal. T cells further showed non-contact mediated increase in calcium level, although this response was delayed compared to contact-mediated signals. Our results suggest that this nanoliter droplet array-based microfluidic platform is a promising technique for assessment of heterogeneity in various types of cellular responses, detection of early/delayed signalling events and live cell phenotyping of immune cells.

Wide allelic heterogeneity with predominance of large IDS gene complex rearrangements in a sample of Mexican patients with Hunter syndrome.

PubMed

Alcántara-Ortigoza, M A; García-de Teresa, B; González-Del Angel, A; Berumen, J; Guardado-Estrada, M; Fernández-Hernández, L; Navarrete-Martínez, J I; Maza-Morales, M; Rius-Domínguez, R

2016-05-01

Hunter syndrome or mucopolysaccharidosis type II (MPSII) is caused by pathogenic variants in the IDS gene. This is the first study that examines the mutational spectrum in 25 unrelated Mexican MPSII families. The responsible genotype was identified in 96% of the families (24/25) with 10 novel pathogenic variants: c.133G>C, c.1003C>T, c.1025A>C, c.463_464delinsCCGTATAGCTGG, c.754_767del, c.1132_1133del, c.1463del, c.508-1G>C, c.1006+1G>T and c.(-217_103del). Extensive IDS gene deletions were identified in four patients; using DNA microarray analysis two patients showed the loss of the entire AFF2 gene, and epilepsy developed in only one of them. Wide allelic heterogeneity was noted, with large gene alterations (e.g. IDS/IDSP1 gene inversions, partial to extensive IDS deletions, and one chimeric IDS-IDSP1 allele) that occurred at higher frequencies than previously reported (36% vs 18.9-29%). The frequency of carrier mothers (80%) is consistent with previous descriptions (>70%). Carrier assignment allowed molecular prenatal diagnoses. Notably, somatic and germline mosaicism was identified in one family, and two patients presented thrombocytopenic purpura and pancytopenia after idursulfase enzyme replacement treatment. Our findings suggest a wide allelic heterogeneity in Mexican MPSII patients; DNA microarray analysis contributes to further delineation of the resulting phenotype for IDS and neighboring loci deletions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A unique combination of 17pter trisomy and 21qter monosomy in a boy with developmental delay, severe intellectual disability, growth retardation and dysmorphisms.

PubMed

Zheng, Zhaojing; Yao, Ru-En; Geng, Juan; Jin, Xingming; Shen, Yongnian; Ying, Daming; Fu, Qihua; Yu, Yongguo

2013-03-10

Microduplication at 17p13.3 and microdeletion at 21q22 are both rare chromosomal aberrations. The presence of both genomic imbalances in one patient has not been previously reported in literature. In this study, we performed a molecular diagnostic testing with a whole genome microarray on a 3-year-old boy with developmental delay, mental retardation and multiple malformations. A routine G-banding karyotype analysis was performed using peripheral lymphocytes. Chromosome microarray analysis (CMA) was done using Affymetrix CytoScan™ HD array. Genomic imbalances were further confirmed by multiple ligation-dependent probe amplification (MLPA). The result of karyotyping was normal but CMA detected a 9.8 Mb microduplication at 17p13.3-13.1 (chr17: 1-9,875,545) and a 2.8 Mb microdeletion involving 21q22.3-qter (chr21: 45,239,077-48,097,372). The imbalances were due to a balanced translocation present in patient's mother. The patient was characterized with short stature, profound developmental delay, non-verbal, intellectual disability as well as craniofacial dysmorphism, subtle brain structural anomaly and sparse scalp hair. This is the first patient reported with a combination of a microduplication at 17p13.3-13.1 and a microdeletion at 21q22.3-qter. Both genomic imbalances were undetected by conventional karyotyping but were delineated with CMA test. Synergistic effect from the two rare genomic imbalances is likely responsible for the severe clinical phenotypes observed in this patient. Copyright © 2012 Elsevier B.V. All rights reserved.

Transfer of chromosome 3 fragments suppresses tumorigenicity of an ovarian cancer cell line monoallelic for chromosome 3p.

PubMed

Cody, N A L; Ouellet, V; Manderson, E N; Quinn, M C J; Filali-Mouhim, A; Tellis, P; Zietarska, M; Provencher, D M; Mes-Masson, A-M; Chevrette, M; Tonin, P N

2007-01-25

Multiple chromosome 3p tumor suppressor genes (TSG) have been proposed in the pathogenesis of ovarian cancer based on complex patterns of 3p loss. To attain functional evidence in support of TSGs and identify candidate regions, we applied a chromosome transfer method involving cell fusions of the tumorigenic OV90 human ovarian cancer cell line, monoallelic for 3p and an irradiated mouse cell line containing a human chromosome 3 in order to derive OV90 hybrids containing normal 3p fragments. The resulting hybrids showed complete or incomplete suppression of tumorigenicity in nude mouse xenograft assays, and varied in their ability to form colonies in soft agarose and three-dimensional spheroids in a manner consistent with alteration of their in vivo tumorigenic phenotypes. Expression microarray analysis identified a set of common differentially expressed genes, such as SPARC, DAB2 and VEGF, some of which have been shown implicated in ovarian cancer. Genotyping assays revealed that they harbored normal 3p fragments, some of which overlapped candidate TSG regions (3p25-p26, 3p24 and 3p14-pcen) identified previously in loss of heterozygosity analyses of ovarian cancers. However, only the 3p12-pcen region was acquired in common by all hybrids where expression microarray analysis identified differentially expressed genes. The correlation of 3p12-pcen transfer and tumor suppression with a concerted re-programming of the cellular transcriptome suggest that the putative TSG may have affected key underlying events in ovarian cancer.

Constitutive expression of a grapevine polygalacturonase-inhibiting protein affects gene expression and cell wall properties in uninfected tobacco

PubMed Central

2011-01-01

Background Polygalacturonase-inhibiting proteins (PGIPs) directly limit the effective ingress of fungal pathogens by inhibiting cell wall-degrading endopolygalacturonases (ePGs). Transgenic tobacco plants over-expressing grapevine (Vitis vinifera) Vvpgip1 have previously been shown to be resistant to Botrytis infection. In this study we characterized two of these PGIP over-expressing lines with known resistance phenotypes by gene expression and hormone profiling in the absence of pathogen infection. Results Global gene expression was performed by a cross-species microarray approach using a potato cDNA microarray. The degree of potential cross-hybridization between probes was modeled by a novel computational workflow designed in-house. Probe annotations were updated by predicting probe-to-transcript hybridizations and combining information derived from other plant species. Comparing uninfected Vvpgip1-overexpressing lines to wild-type (WT), 318 probes showed significant change in expression. Functional groups of genes involved in metabolism and associated to the cell wall were identified and consequent cell wall analysis revealed increased lignin-levels in the transgenic lines, but no major differences in cell wall-derived polysaccharides. GO enrichment analysis also identified genes responsive to auxin, which was supported by elevated indole-acetic acid (IAA) levels in the transgenic lines. Finally, a down-regulation of xyloglucan endotransglycosylase/hydrolases (XTHs), which are important in cell wall remodeling, was linked to a decrease in total XTH activity. Conclusions This evaluation of PGIP over-expressing plants performed under pathogen-free conditions to exclude the classical PGIP-ePG inhibition interaction indicates additional roles for PGIPs beyond the inhibition of ePGs. PMID:22078230

The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

ERIC Educational Resources Information Center

Beaudet, Arthur L.

2013-01-01

Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

PubMed Central

2011-01-01

Background Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence in situ hybridization (FISH). Results Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23. Conclusions Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future. PMID:22087757

DNA Modification Study of Major Depressive Disorder: Beyond Locus-by-Locus Comparisons

PubMed Central

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A.; Kwan, Andrew; Kaminsky, Zachary A.; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L.; Gottesman, Irving I.; Willemsen, Gonneke; de Geus, Eco J.C.; Vink, Jacqueline M.; Slagboom, P. Eline; Wray, Naomi R.; Heath, Andrew C.; Montgomery, Grant W.; Turecki, Gustavo; Martin, Nicholas G.; Boomsma, Dorret I.; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2014-01-01

Background Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. Methods We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. Results In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Conclusions Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. PMID:25108803

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

PubMed

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

2018-01-01

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

Identification of PblB mediating galactose-specific adhesion in a successful Streptococcus pneumoniae clone

PubMed Central

Hsieh, Yu-Chia; Lin, Tzu-Lung; Lin, Che-Ming; Wang, Jin-Town

2015-01-01

The pneumococcal genome is variable and there are minimal data on the influence of the accessory genome on phenotype. Pneumococcal serotype 14 sequence type (ST) 46 had been the most prevalent clone causing pneumonia in children in Taiwan. A microarray was constructed using the genomic DNA of a clinical strain (NTUH-P15) of serotype 14 ST46. Using DNA hybridization, genomic variations in NTUH-P15 were compared to those of 3 control strains. Microarray analysis identified 7 genomic regions that had significant increases in hybridization signals in the NTUH-P15 strain compared to control strains. One of these regions encoded PblB, a phage-encoded virulence factor implicated (in Streptococcus mitis) in infective endocarditis. The isogenic pblB mutant decreased adherence to A549 human lung epithelial cell compared to wild-type NTUH-P15 strain (P = 0.01). Complementation with pblB restored the adherence. PblB is predicted to contain a galactose-binding domain-like region. Preincubation of NTUH-P15 with D-galactose resulted in decreases of adherence to A549 cell in a dose-dependent manner. Challenge of mice with NTUH-P15, isogenic pblB mutant and pblB complementation strains determined that PblB was required for bacterial persistence in the nasopharynx and lung. PblB, as an adhesin mediating the galactose-specific adhesion activity of pneumococci, promote pneumococcal clonal success. PMID:26193794

DNA modification study of major depressive disorder: beyond locus-by-locus comparisons.

PubMed

Oh, Gabriel; Wang, Sun-Chong; Pal, Mrinal; Chen, Zheng Fei; Khare, Tarang; Tochigi, Mamoru; Ng, Catherine; Yang, Yeqing A; Kwan, Andrew; Kaminsky, Zachary A; Mill, Jonathan; Gunasinghe, Cerisse; Tackett, Jennifer L; Gottesman, Irving I; Willemsen, Gonneke; de Geus, Eco J C; Vink, Jacqueline M; Slagboom, P Eline; Wray, Naomi R; Heath, Andrew C; Montgomery, Grant W; Turecki, Gustavo; Martin, Nicholas G; Boomsma, Dorret I; McGuffin, Peter; Kustra, Rafal; Petronis, Art

2015-02-01

Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations. Copyright © 2015 Society of Biological Psychiatry. All rights reserved.

Transcriptomic Responses of Atlantic Salmon (Salmo salar) to Environmental Enrichment during Juvenile Rearing

PubMed Central

Evans, Melissa L.; Hori, Tiago S.; Rise, Matthew L.; Fleming, Ian A.

2015-01-01

Captive rearing programs (hatcheries) are often used in conservation and management efforts for at-risk salmonid fish populations. However, hatcheries typically rear juveniles in environments that contrast starkly with natural conditions, which may lead to phenotypic and/or genetic changes that adversely affect the performance of juveniles upon their release to the wild. Environmental enrichment has been proposed as a mechanism to improve the efficacy of population restoration efforts from captive-rearing programs; in this study, we examine the influence of environmental enrichment during embryo and yolk-sac larval rearing on the transcriptome of Atlantic salmon (Salmo salar). Full siblings were reared in either a hatchery environment devoid of structure or an environment enriched with gravel substrate. At the end of endogenous feeding by juveniles, we examined patterns of gene transcript abundance in head tissues using the cGRASP-designed Agilent 4×44K microarray. Significance analysis of microarrays (SAM) indicated that 808 genes were differentially transcribed between the rearing environments and a total of 184 gene ontological (GO) terms were over- or under-represented in this gene list, several associated with mitosis/cell cycle and muscle and heart development. There were also pronounced differences among families in the degree of transcriptional response to rearing environment enrichment, suggesting that gene-by-environment effects, possibly related to parental origin, could influence the efficacy of enrichment interventions. PMID:25742646

Transcriptomic responses of Atlantic salmon (Salmo salar) to environmental enrichment during juvenile rearing.

PubMed

Evans, Melissa L; Hori, Tiago S; Rise, Matthew L; Fleming, Ian A

2015-01-01

Captive rearing programs (hatcheries) are often used in conservation and management efforts for at-risk salmonid fish populations. However, hatcheries typically rear juveniles in environments that contrast starkly with natural conditions, which may lead to phenotypic and/or genetic changes that adversely affect the performance of juveniles upon their release to the wild. Environmental enrichment has been proposed as a mechanism to improve the efficacy of population restoration efforts from captive-rearing programs; in this study, we examine the influence of environmental enrichment during embryo and yolk-sac larval rearing on the transcriptome of Atlantic salmon (Salmo salar). Full siblings were reared in either a hatchery environment devoid of structure or an environment enriched with gravel substrate. At the end of endogenous feeding by juveniles, we examined patterns of gene transcript abundance in head tissues using the cGRASP-designed Agilent 4×44K microarray. Significance analysis of microarrays (SAM) indicated that 808 genes were differentially transcribed between the rearing environments and a total of 184 gene ontological (GO) terms were over- or under-represented in this gene list, several associated with mitosis/cell cycle and muscle and heart development. There were also pronounced differences among families in the degree of transcriptional response to rearing environment enrichment, suggesting that gene-by-environment effects, possibly related to parental origin, could influence the efficacy of enrichment interventions.

Microarray mRNA expression analysis of Fanconi anemia fibroblasts.

PubMed

Galetzka, D; Weis, E; Rittner, G; Schindler, D; Haaf, T

2008-01-01

Fanconi anemia (FA) cells are generally hypersensitive to DNA cross-linking agents, implying that mutations in the different FANC genes cause a similar DNA repair defect(s). By using a customized cDNA microarray chip for DNA repair- and cell cycle-associated genes, we identified three genes, cathepsin B (CTSB), glutaredoxin (GLRX), and polo-like kinase 2 (PLK2), that were misregulated in untreated primary fibroblasts from three unrelated FA-D2 patients, compared to six controls. Quantitative real-time RT PCR was used to validate these results and to study possible molecular links between FA-D2 and other FA subtypes. GLRX was misregulated to opposite directions in a variety of different FA subtypes. Increased CTSB and decreased PLK2 expression was found in all or almost all of the analyzed complementation groups and, therefore, may be related to the defective FA pathway. Transcriptional upregulation of the CTSB proteinase appears to be a secondary phenomenon due to proliferation differences between FA and normal fibroblast cultures. In contrast, PLK2 is known to play a pivotal role in processes that are linked to FA defects and may contribute in multiple ways to the FA phenotype: PLK2 is a target gene for TP53, is likely to function as a tumor suppressor gene in hematologic neoplasia, and Plk2(-/-) mice are small because of defective embryonal development. (c) 2008 S. Karger AG, Basel.

Pathogen profiling for disease management and surveillance.

PubMed

Sintchenko, Vitali; Iredell, Jonathan R; Gilbert, Gwendolyn L

2007-06-01

The usefulness of rapid pathogen genotyping is widely recognized, but its effective interpretation and application requires integration into clinical and public health decision-making. How can pathogen genotyping data best be translated to inform disease management and surveillance? Pathogen profiling integrates microbial genomics data into communicable disease control by consolidating phenotypic identity-based methods with DNA microarrays, proteomics, metabolomics and sequence-based typing. Sharing data on pathogen profiles should facilitate our understanding of transmission patterns and the dynamics of epidemics.

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

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

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Clinical diagnostic exome evaluation for an infant with a lethal disorder: genetic diagnosis of TARP syndrome and expansion of the phenotype in a patient with a newly reported RBM10 alteration.

PubMed

Powis, Zöe; Hart, Alexa; Cherny, Sara; Petrik, Igor; Palmaer, Erika; Tang, Sha; Jones, Carolyn

2017-06-02

Diagnostic Exome Sequencing (DES) has been shown to be an effective tool for diagnosis individuals with suspected genetic conditions. We report a male infant born with multiple anomalies including bilateral dysplastic kidneys, cleft palate, bilateral talipes, and bilateral absence of thumbs and first toes. Prenatal testing including chromosome analysis and microarray did not identify a cause for the multiple congenital anomalies. Postnatal diagnostic exome studies (DES) were utilized to find a molecular diagnosis for the patient. Exome sequencing of the proband, mother, and father showed a previously unreported maternally inherited RNA binding motif protein 10 (RBM10) c.1352_1353delAG (p.E451Vfs*66) alteration. Mutations in RBM10 are associated with TARP syndrome, an X-linked recessive disorder originally described with cardinal features of talipes equinovarus, atrial septal defect, Robin sequence, and persistent left superior vena cava. DES established a molecular genetic diagnosis of TARP syndrome for a neonatal patient with a poor prognosis in whom traditional testing methods were uninformative and allowed for efficient diagnosis and future reproductive options for the parents. Other reported cases of TARP syndrome demonstrate significant variability in clinical phenotype. The reported features in this infant including multiple hemivertebrae, imperforate anus, aplasia of thumbs and first toes have not been reported in previous patients, thus expanding the clinical phenotype for this rare disorder.

Epigenetic regulation of EFEMP1 in prostate cancer: biological relevance and clinical potential

PubMed Central

Almeida, Mafalda; Costa, Vera L; Costa, Natália R; Ramalho-Carvalho, João; Baptista, Tiago; Ribeiro, Franclim R; Paulo, Paula; Teixeira, Manuel R; Oliveira, Jorge; Lothe, Ragnhild A; Lind, Guro E; Henrique, Rui; Jerónimo, Carmen

2014-01-01

Epigenetic alterations are common in prostate cancer (PCa) and seem to contribute decisively to its initiation and progression. Moreover, aberrant promoter methylation is a promising biomarker for non-invasive screening. Herein, we sought to characterize EFEMP1 as biomarker for PCa, unveiling its biological relevance in prostate carcinogenesis. Microarray analyses of treated PCa cell lines and primary tissues enabled the selection of differentially methylated genes, among which EFEMP1 was further validated by MSP and bisulfite sequencing. Assessment of biomarker performance was accomplished by qMSP. Expression analysis of EFEMP1 and characterization of histone marks were performed in tissue samples and cancer cell lines to determine the impact of epigenetic mechanisms on EFEMP1 transcriptional regulation. Phenotypic assays, using transfected cell lines, permitted the evaluation of EFEMP1’s role in PCa development. EFEMP1 methylation assay discriminated PCa from normal prostate tissue (NPT; P < 0.001, Kruskall–Wallis test) and renal and bladder cancers (96% sensitivity and 98% specificity). EFEMP1 transcription levels inversely correlated with promoter methylation and histone deacetylation, suggesting that both epigenetic mechanisms are involved in gene regulation. Phenotypic assays showed that EFEMP1 de novo expression reduces malignant phenotype of PCa cells. EFEMP1 promoter methylation is prevalent in PCa and accurately discriminates PCa from non-cancerous prostate tissues and other urological neoplasms. This epigenetic alteration occurs early in prostate carcinogenesis and, in association with histone deacetylation, progressively leads to gene down-regulation, fostering cell proliferation, invasion and evasion of apoptosis. PMID:25211630

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.

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.

Phenotypic Diversification Is Associated with Host-Induced Transposon Derepression in the Sudden Oak Death Pathogen Phytophthora ramorum

PubMed Central

Kasuga, Takao; Kozanitas, Melina; Bui, Mai; Hüberli, Daniel; Rizzo, David M.; Garbelotto, Matteo

2012-01-01

The oomycete pathogen Phytophthora ramorum is responsible for sudden oak death (SOD) in California coastal forests. P. ramorum is a generalist pathogen with over 100 known host species. Three or four closely related genotypes of P. ramorum (from a single lineage) were originally introduced in California forests and the pathogen reproduces clonally. Because of this the genetic diversity of P. ramorum is extremely low in Californian forests. However, P. ramorum shows diverse phenotypic variation in colony morphology, colony senescence, and virulence. In this study, we show that phenotypic variation among isolates is associated with the host species from which the microbe was originally cultured. Microarray global mRNA profiling detected derepression of transposable elements (TEs) and down-regulation of crinkler effector homologs (CRNs) in the majority of isolates originating from coast live oak (Quercus agrifolia), but this expression pattern was not observed in isolates from California bay laurel (Umbellularia californica). In some instances, oak and bay laurel isolates originating from the same geographic location had identical genotypes based on multilocus simples sequence repeat (SSR) marker analysis but had different phenotypes. Expression levels of the two marker genes analyzed by quantitative reverse transcription PCR were correlated with originating host species, but not with multilocus genotypes. Because oak is a nontransmissive dead-end host for P. ramorum, our observations are congruent with an epi-transposon hypothesis; that is, physiological stress is triggered on P. ramorum while colonizing oak stems and disrupts epigenetic silencing of TEs. This then results in TE reactivation and possibly genome diversification without significant epidemiological consequences. We propose the P. ramorum-oak host system in California forests as an ad hoc model for epi-transposon mediated diversification. PMID:22529930

Ionotropic glutamate receptors mediate inducible defense in the water flea Daphnia pulex.

PubMed

Miyakawa, Hitoshi; Sato, Masanao; Colbourne, John K; Iguchi, Taisen

2015-01-01

Phenotypic plasticity is the ability held in many organisms to produce different phenotypes with a given genome in response to environmental stimuli, such as temperature, nutrition and various biological interactions. It seems likely that environmental signals induce a variety of mechanistic responses that influence ontogenetic processes. Inducible defenses, in which prey animals alter their morphology, behavior and/or other traits to help protect against direct or latent predation threats, are among the most striking examples of phenotypic plasticity. The freshwater microcrustacean Daphnia pulex forms tooth-like defensive structures, "neckteeth," in response to chemical cues or signals, referred to as "kairomones," in this case released from phantom midge larvae, a predator of D. pulex. To identify factors involved in the reception and/or transmission of a kairomone, we used microarray analysis to identify genes up-regulated following a short period of exposure to the midge kairomone. In addition to identifying differentially expressed genes of unknown function, we also found significant up-regulation of genes encoding ionotropic glutamate receptors, which are known to be involved in neurotransmission in many animal species. Specific antagonists of these receptors strongly inhibit the formation of neckteeth in D. pulex, although agonists did not induce neckteeth by themselves, indicating that ionotropic glutamate receptors are necessary but not sufficient for early steps of neckteeth formation in D. pulex. Moreover, using co-exposure of D. pulex to antagonists and juvenile hormone (JH), which physiologically mediates neckteeth formation, we found evidence suggesting that the inhibitory effect of antagonists is not due to direct inhibition of JH synthesis/secretion. Our findings not only provide a candidate molecule required for the inducible defense response in D. pulex, but also will contribute to the understanding of complex mechanisms underlying the recognition of environmental changes, which form the basis of phenotypic plasticity.

Microevolution of Group A Streptococci In Vivo: Capturing Regulatory Networks Engaged in Sociomicrobiology, Niche Adaptation, and Hypervirulence

PubMed Central

Aziz, Ramy K.; Kansal, Rita; Aronow, Bruce J.; Taylor, William L.; Rowe, Sarah L.; Kubal, Michael; Chhatwal, Gursharan S.; Walker, Mark J.; Kotb, Malak

2010-01-01

The onset of infection and the switch from primary to secondary niches are dramatic environmental changes that not only alter bacterial transcriptional programs, but also perturb their sociomicrobiology, often driving minor subpopulations with mutant phenotypes to prevail in specific niches. Having previously reported that M1T1 Streptococcus pyogenes become hypervirulent in mice due to selection of mutants in the covRS regulatory genes, we set out to dissect the impact of these mutations in vitro and in vivo from the impact of other adaptive events. Using a murine subcutaneous chamber model to sample the bacteria prior to selection or expansion of mutants, we compared gene expression dynamics of wild type (WT) and previously isolated animal-passaged (AP) covS mutant bacteria both in vitro and in vivo, and we found extensive transcriptional alterations of pathoadaptive and metabolic gene sets associated with invasion, immune evasion, tissue-dissemination, and metabolic reprogramming. In contrast to the virulence-associated differences between WT and AP bacteria, Phenotype Microarray analysis showed minor in vitro phenotypic differences between the two isogenic variants. Additionally, our results reflect that WT bacteria's rapid host-adaptive transcriptional reprogramming was not sufficient for their survival, and they were outnumbered by hypervirulent covS mutants with SpeB−/Sdahigh phenotype, which survived up to 14 days in mice chambers. Our findings demonstrate the engagement of unique regulatory modules in niche adaptation, implicate a critical role for bacterial genetic heterogeneity that surpasses transcriptional in vivo adaptation, and portray the dynamics underlying the selection of hypervirulent covS mutants over their parental WT cells. PMID:20418946

Comparative Genotypic and Phenotypic Analysis of Cronobacter Species Cultured from Four Powdered Infant Formula Production Facilities: Indication of Pathoadaptation along the Food Chain

PubMed Central

Yan, Qiongqiong; Wang, Juan; Gangiredla, Jayanthi; Cao, Yu; Martins, Marta; Gopinath, Gopal R.; Stephan, Roger; Lampel, Keith; Tall, Ben D.

2015-01-01

Cronobacter species are opportunistic pathogens commonly found in the environment. Among the seven Cronobacter species, Cronobacter sakazakii sequence type 4 (ST-4) is predominantly associated with recorded cases of infantile meningitis. This study reports on a 26-month powdered infant formula (PIF) surveillance program in four production facilities located in distinct geographic regions. The objective was to identify the ST(s) in PIF production environments and to investigate the phenotypic features that support their survival. Of all 168 Cronobacter isolates, 133 were recovered from a PIF production environment, 31 were of clinical origin, and 4 were laboratory type strains. Sequence type 1 (n = 84 isolates; 63.9%) was the dominant type in PIF production environments. The majority of these isolates clustered with an indistinguishable pulsotype and persisted for at least an 18-month period. Moreover, DNA microarray results identified two phylogenetic lineages among ST-4 strains tested. Thereafter, the ST-1 and -4 isolates were phenotypically compared. Differences were noted based on the phenotypes expressed by these isolates. The ST-1 PIF isolates produced stronger biofilms at both 28°C and 37°C, while the ST-4 clinical isolates exhibited greater swimming activity and increased binding to Congo red dye. Given the fact that PIF is a low-moisture environment and that the clinical environment provides for an interaction between the pathogen and its host, these differences may be consistent with a form of pathoadaptation. These findings help to extend our current understanding of the epidemiology and ecology of Cronobacter species in PIF production environments. PMID:25911470

Recovering from iron deficiency chlorosis in near-isogenic soybeans: a microarray study.

PubMed

O'Rourke, Jamie A; Graham, Michelle A; Vodkin, Lila; Gonzalez, Delkin Orlando; Cianzio, Silvia R; Shoemaker, Randy C

2007-05-01

Iron deficiency chlorosis (IDC) in soybeans has proven to be a perennial problem in the calcareous soils of the U.S. upper Midwest. A historically difficult trait to study in fields, the use of hydroponics in a controlled greenhouse environment has provided a mechanism to study genetic variation while limiting environmental complications. IDC susceptible plants growing in calcareous soils and in iron-controlled hydroponic experiments often exhibit a characteristic chlorotic phenotype early in the growing season but are able to re-green later in the season. To examine the changes in gene expression of these plants, near-isogenic lines, iron efficient PI548553 (Clark) and iron inefficient PI547430 (IsoClark), developed for their response to iron deficiency stress [USDA, ARS, National Genetic Resources Program, Germplasm Resources Information Network - GRIN. (Online Database) National Germplasm Resources Laboratory, Beltsville, MD, 2004. Available: http://www.ars.grin.gov/cgi-bin/npgs/html/acc_search.pl?accid=PI+547430. [22] were grown in iron-deficient hydroponic conditions for one week, then transferred to iron sufficient conditions for another week. This induced a phenotypic response mimicking the growth of the plants in the field; initial chlorosis followed by re-greening. RNA was isolated from root tissue and transcript profiles were examined between the two near-isogenic lines using publicly available cDNA microarrays. By alleviating the iron deficiency stress our expectation was that plants would return to baseline expression levels. However, the microarray comparison identified four cDNAs that were under-expressed by a two-fold or greater difference in the iron inefficient plant compared to the iron efficient plant. This differential expression was re-examined and confirmed by real time PCR experimentation. Control experiments showed that these genes are not differentially expressed in plants grown continually under iron rich hydroponic conditions. The expression differences suggest potential residual effects of iron deficiency on plant health.

The search for the neurobiological basis of vulnerability to drug abuse: using microarrays to investigate the role of stress and individual differences.

PubMed

Kabbaj, M; Evans, S; Watson, S J; Akil, H

2004-01-01

Basic neurobiological studies have led to great progress in our understanding of the mechanisms of action of drugs of abuse. Much has been learned about the brain response from the moment a psychoactive drug enters the organism onwards, including the psychological, neurobiological and peripheral effects of repeated drug administration, withdrawal and re-exposure. However, to relate this knowledge to the human experience requires further research on the antecedents of drug-taking behavior and the factors that predispose particular individuals to drug seeking and drug abuse. Thus, it is important to address several issues at the fundamental level: (1) Why are some individuals more vulnerable to drugs of abuse more than others? Is there a broader dimension or dimensions of emotional reactivity that contribute to this difference in vulnerability? (2) What is the effect of psychosocial stress on drug-seeking and drug-taking behavior, and are the effects distinct across individuals? (3) Since both drug-taking behavior and stress have sustained and pervasive effects on the brain, can we use microarrays to discern the "neural signature" or "neural phenotype" associated with these processes, and can we distinguish this signature across individuals with differing propensities to taking drugs? In the present paper, we summarize some of our early attempts at addressing these questions. We rely on animal studies aimed at characterizing the emotional and stress reactivity of rats with different propensities to self-administer drugs (high responders and low responders); we briefly describe the effect of a psychosocial stressor on these animals; we then detail a study using microarray technology aimed at investigating the "neural phenotype" associated with social defeat stress in the high vs. low responder animals. This "discovery" approach is used as a starting place for identifying novel mechanisms that might alter the vulnerability of different individuals to drug-seeking behavior. The power and limits of this approach, and its future directions, are discussed within this general framework.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

PubMed Central

Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

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.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

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.

Microarray-based screening of heat shock protein inhibitors.

PubMed

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

2014-06-20

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

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

PubMed Central

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

2015-01-01

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

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

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.

Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress.

PubMed

Jo, Kyuri; Kwon, Hawk-Bin; Kim, Sun

2014-06-01

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how organisms react to stress conditions over time. Thus many biologists routinely measure whole genome level gene expressions at multiple time points. However, there are several technical difficulties for analyzing such whole genome expression data. In addition, these days gene expression data is often measured by using RNA-sequencing rather than microarray technologies and then analysis of expression data is much more complicated since the analysis process should start with mapping short reads and produce differentially activated pathways and also possibly interactions among pathways. In addition, many useful tools for analyzing microarray gene expression data are not applicable for the RNA-seq data. Thus a comprehensive package for analyzing time series transcriptome data is much needed. In this article, we present a comprehensive package, Time-series RNA-seq Analysis Package (TRAP), integrating all necessary tasks such as mapping short reads, measuring gene expression levels, finding differentially expressed genes (DEGs), clustering and pathway analysis for time-series data in a single environment. In addition to implementing useful algorithms that are not available for RNA-seq data, we extended existing pathway analysis methods, ORA and SPIA, for time series analysis and estimates statistical values for combined dataset by an advanced metric. TRAP also produces visual summary of pathway interactions. Gene expression change labeling, a practical clustering method used in TRAP, enables more accurate interpretation of the data when combined with pathway analysis. We applied our methods on a real dataset for the analysis of rice (Oryza sativa L. Japonica nipponbare) upon drought stress. The result showed that TRAP was able to detect pathways more accurately than several existing methods. TRAP is available at http://biohealth.snu.ac.kr/software/TRAP/. Copyright © 2014 Elsevier Inc. All rights reserved.

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

PubMed

Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark

2006-12-18

Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.

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.

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

PubMed

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

2008-01-01

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

Differential immune gene expression profiles in susceptible and resistant full-sibling families of Atlantic salmon (Salmo salar) challenged with infectious pancreatic necrosis virus (IPNV).

PubMed

Reyes-López, Felipe E; Romeo, Jose S; Vallejos-Vidal, Eva; Reyes-Cerpa, Sebastián; Sandino, Ana M; Tort, Lluis; Mackenzie, Simon; Imarai, Mónica

2015-11-01

This study aims to identify at the expression level the immune-related genes associated with IPN-susceptible and resistant phenotypes in Atlantic salmon full-sibling families. We have analyzed thirty full-sibling families infected by immersion with IPNV and then classified as resistant or susceptible using a multivariate survival analysis based on a gamma-Cox frailty model and the Kaplan-Meier mortality curves. In four families within each group head kidneys were pooled for real-time PCR and one-color salmon-specific oligonucleotide microarray (21K) analysis at day 1 and 5 post-infection. Transcripts involved in innate response (IL-6, IFN-α), antigen presentation (HSP-70, HSP-90, MHC-I), TH1 response (IL-12, IFN-γ, CRFB6), immunosuppression (IL-10, TGF-β1) and leukocyte activation and migration (CCL-19, CD18) showed a differential expression pattern between both phenotypes, except in IL-6. In susceptible families, except for IFN-γ, the expressions dropped to basal values at day 5 post-infection. In resistant families, unlike susceptible families, levels remained high or increased (except for IL-6) at day 5. Transcriptomic analysis showed that both families have a clear differential expression pattern, resulting in a marked down-regulation in immune related genes involved in innate response, complement system, antigen recognition and activation of immune response in IPN-resistant. Down-regulation of genes, mainly related to tissue differentiation and protein degradation metabolism, was also observed in resistant families. We have identified an immune-related gene patterns associated with susceptibility and resistance to IPNV infection of Atlantic salmon. This suggests that a limited immune response is associated with resistant fish phenotype to IPNV challenge while a highly inflammatory but short response is associated with susceptibility. Copyright © 2015 Elsevier Ltd. All rights reserved.

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

High-throughput investigation of endothelial-to-mesenchymal transformation (EndMT) with combinatorial cellular microarrays.

PubMed

Wang, Zongjie; Calpe, Blaise; Zerdani, Jalil; Lee, Youngsang; Oh, Jonghyun; Bae, Hojae; Khademhosseini, Ali; Kim, Keekyoung

2016-07-01

In the developing heart, a specific subset of endocardium undergoes an endothelial-to-mesenchymal transformation (EndMT) thus forming nascent valve leaflets. Extracellular matrix (ECM) proteins and growth factors (GFs) play important roles in regulating EndMT but the combinatorial effect of GFs with ECM proteins is less well understood. Here we use microscale engineering techniques to create single, binary, and tertiary component microenvironments to investigate the combinatorial effects of ECM proteins and GFs on the attachment and transformation of adult ovine mitral valve endothelial cells to a mesenchymal phenotype. With the combinatorial microenvironment microarrays, we utilized 60 different combinations of ECM proteins (Fibronectin, Collagen I, II, IV, Laminin) and GFs (TGF-β1, bFGF, VEGF) and were able to identify new microenvironmental conditions capable of modulating EndMT in MVECs. Experimental results indicated that TGF-β1 significantly upregulated the EndMT while either bFGF or VEGF downregulated EndMT process markedly. Also, ECM proteins could influence both the attachment of MVECs and the response of MVECs to GFs. In terms of attachment, fibronectin is significantly better for the adhesion of MVECs among the five tested proteins. Overall collagen IV and fibronectin appeared to play important roles in promoting EndMT process. Great consistency between macroscale and microarrayed experiments and present studies demonstrates that high-throughput cellular microarrays are a promising approach to study the regulation of EndMT in valvular endothelium. Biotechnol. Bioeng. 2016;113: 1403-1412. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

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

Genome-Wide Search Reveals the Existence of a Limited Number of Thyroid Hormone Receptor Alpha Target Genes in Cerebellar Neurons

PubMed Central

Chatonnet, Fabrice; Guyot, Romain; Picou, Frédéric; Bondesson, Maria; Flamant, Frederic

2012-01-01

Thyroid hormone (T3) has a major influence on cerebellum post-natal development. The major phenotypic landmark of exposure to low levels of T3 during development (hypothyroidism) in the cerebellum is the retarded inward migration of the most numerous cell type, granular neurons. In order to identify the direct genetic regulation exerted by T3 on cerebellar neurons and their precursors, we used microarray RNA hybridization to perform a time course analysis of T3 induced gene expression in primary cultures of cerebellar neuronal cell. These experiments suggest that we identified a small set of genes which are directly regulated, both in vivo and in vitro, during cerebellum post-natal development. These modest changes suggest that T3 does not acts directly on granular neurons and mainly indirectly influences the cellular interactions taking place during development. PMID:22586439

xQTL workbench: a scalable web environment for multi-level QTL analysis.

PubMed

Arends, Danny; van der Velde, K Joeri; Prins, Pjotr; Broman, Karl W; Möller, Steffen; Jansen, Ritsert C; Swertz, Morris A

2012-04-01

xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. m.a.swertz@rug.nl.

xQTL workbench: a scalable web environment for multi-level QTL analysis

PubMed Central

Arends, Danny; van der Velde, K. Joeri; Prins, Pjotr; Broman, Karl W.; Möller, Steffen; Jansen, Ritsert C.; Swertz, Morris A.

2012-01-01

Summary: xQTL workbench is a scalable web platform for the mapping of quantitative trait loci (QTLs) at multiple levels: for example gene expression (eQTL), protein abundance (pQTL), metabolite abundance (mQTL) and phenotype (phQTL) data. Popular QTL mapping methods for model organism and human populations are accessible via the web user interface. Large calculations scale easily on to multi-core computers, clusters and Cloud. All data involved can be uploaded and queried online: markers, genotypes, microarrays, NGS, LC-MS, GC-MS, NMR, etc. When new data types come available, xQTL workbench is quickly customized using the Molgenis software generator. Availability: xQTL workbench runs on all common platforms, including Linux, Mac OS X and Windows. An online demo system, installation guide, tutorials, software and source code are available under the LGPL3 license from http://www.xqtl.org. Contact: m.a.swertz@rug.nl PMID:22308096

The sensor kinase PhoQ mediates virulence in Pseudomonas aeruginosa.

PubMed

Gooderham, W James; Gellatly, Shaan L; Sanschagrin, François; McPhee, Joseph B; Bains, Manjeet; Cosseau, Celine; Levesque, Roger C; Hancock, Robert E W

2009-03-01

Pseudomonas aeruginosa is a ubiquitous environmental Gram-negative bacterium that is also a major opportunistic human pathogen in nosocomial infections and cystic fibrosis chronic lung infections. PhoP-PhoQ is a two-component regulatory system that has been identified as essential for virulence and cationic antimicrobial peptide resistance in several other Gram-negative bacteria. This study demonstrated that mutation of phoQ caused reduced twitching motility, biofilm formation and rapid attachment to surfaces, 2.2-fold reduced cytotoxicity to human lung epithelial cells, substantially reduced lettuce leaf virulence, and a major, 10 000-fold reduction in competitiveness in chronic rat lung infections. Microarray analysis revealed that PhoQ controlled the expression of many genes consistent with these phenotypes and with its known role in polymyxin B resistance. It was also demonstrated that PhoQ controls the expression of many genes outside the known PhoP regulon.

22q11.2q13 duplication including SOX10 causes sex-reversal and peripheral demyelinating neuropathy, central dysmyelinating leukodystrophy, Waardenburg syndrome, and Hirschsprung disease.

PubMed

Falah, Nadia; Posey, Jennifer E; Thorson, Willa; Benke, Paul; Tekin, Mustafa; Tarshish, Brocha; Lupski, James R; Harel, Tamar

2017-04-01

Diagnosis of genetic syndromes may be difficult when specific components of a disorder manifest at a later age. We present a follow up of a previous report [Seeherunvong et al., (2004); AJMGA 127: 149-151], of an individual with 22q duplication and sex-reversal syndrome. The subject's phenotype evolved to include peripheral and central demyelination, Waardenburg syndrome type IV, and Hirschsprung disease (PCWH; MIM 609136). DNA microarray analysis defined the duplication at 22q11.2q13, including SOX10. Sequencing of the coding region of SOX10 did not reveal any mutations. Our data suggest that SOX10 duplication can cause disorders of sex development and PCWH, supporting the hypothesis that SOX10 toxic gain of function rather than dominant negative activity underlies PCWH. © 2017 Wiley Periodicals, Inc.

22q11.2q13 Duplication Including SOX10 causes Sex-reversal and Peripheral Demyelinating Neuropathy, Central Dysmyelinating Leukodystrophy, Waardenburg Syndrome and Hirschsprung Disease

PubMed Central

Falah, Nadia; Posey, Jennifer E.; Thorson, Willa; Benke, Paul; Tekin, Mustafa; Tarshish, Brocha; Lupski, James R; Harel, Tamar

2017-01-01

Diagnosis of genetic syndromes may be difficult when specific components of a disorder manifest at a later age. We present a follow up of a previous report [Seeherunvong et al., 2004; Ajmga 127: 149–151], of an individual with 22q duplication and sex-reversal syndrome. The subject’s phenotype evolved to include peripheral and central demyelination, Waardenburg syndrome type IV, and Hirschsprung disease (PCWH; MIM 609136). DNA microarray analysis defined the duplication at 22q11.2q13, including SOX10. Sequencing of the coding region of SOX10 did not reveal any mutations. Our data suggest that SOX10 duplication can cause disorders of sex development and PCWH, supporting the hypothesis that SOX10 toxic gain-of-function rather than dominant negative activity underlies PCWH. PMID:28328136

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

Gene expression in developing watermelon fruit

PubMed Central

Wechter, W Patrick; Levi, Amnon; Harris, Karen R; Davis, Angela R; Fei, Zhangjun; Katzir, Nurit; Giovannoni, James J; Salman-Minkov, Ayelet; Hernandez, Alvaro; Thimmapuram, Jyothi; Tadmor, Yaakov; Portnoy, Vitaly; Trebitsh, Tova

2008-01-01

Background Cultivated watermelon form large fruits that are highly variable in size, shape, color, and content, yet have extremely narrow genetic diversity. Whereas a plethora of genes involved in cell wall metabolism, ethylene biosynthesis, fruit softening, and secondary metabolism during fruit development and ripening have been identified in other plant species, little is known of the genes involved in these processes in watermelon. A microarray and quantitative Real-Time PCR-based study was conducted in watermelon [Citrullus lanatus (Thunb.) Matsum. & Nakai var. lanatus] in order to elucidate the flow of events associated with fruit development and ripening in this species. RNA from three different maturation stages of watermelon fruits, as well as leaf, were collected from field grown plants during three consecutive years, and analyzed for gene expression using high-density photolithography microarrays and quantitative PCR. Results High-density photolithography arrays, composed of probes of 832 EST-unigenes from a subtracted, fruit development, cDNA library of watermelon were utilized to examine gene expression at three distinct time-points in watermelon fruit development. Analysis was performed with field-grown fruits over three consecutive growing seasons. Microarray analysis identified three hundred and thirty-five unique ESTs that are differentially regulated by at least two-fold in watermelon fruits during the early, ripening, or mature stage when compared to leaf. Of the 335 ESTs identified, 211 share significant homology with known gene products and 96 had no significant matches with any database accession. Of the modulated watermelon ESTs related to annotated genes, a significant number were found to be associated with or involved in the vascular system, carotenoid biosynthesis, transcriptional regulation, pathogen and stress response, and ethylene biosynthesis. Ethylene bioassays, performed with a closely related watermelon genotype with a similar phenotype, i.e. seeded, bright red flesh, dark green rind, etc., determined that ethylene levels were highest during the green fruit stage followed by a decrease during the white and pink fruit stages. Additionally, quantitative Real-Time PCR was used to validate modulation of 127 ESTs that were differentially expressed in developing and ripening fruits based on array analysis. Conclusion This study identified numerous ESTs with putative involvement in the watermelon fruit developmental and ripening process, in particular the involvement of the vascular system and ethylene. The production of ethylene during fruit development in watermelon gives further support to the role of ethylene in fruit development in non-climacteric fruits. PMID:18534026

MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

EPA Science Inventory

Microarray Data Analysis Using Multiple Statistical Models

Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

Parents' Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Reiff, Marian; Giarelli, Ellen; Bernhardt, Barbara A.; Easley, Ebony; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

2015-01-01

Clinical guidelines recommend chromosomal microarray analysis (CMA) for all children with autism spectrum disorders (ASDs). We explored the test's perceived usefulness among parents of children with ASD who had undergone CMA, and received a result categorized as pathogenic, variant of uncertain significance, or negative. Fifty-seven parents…

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

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.

cluML: A markup language for clustering and cluster validity assessment of microarray data.

PubMed

Bolshakova, Nadia; Cunningham, Pádraig

2005-01-01

cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

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.

Cross species analysis of microarray expression data

PubMed Central

Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv

2009-01-01

Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096

Separation and Analysis of Adherent and Non-Adherent Cancer Cells Using a Single-Cell Microarray Chip.

PubMed

Yamamura, Shohei; Yamada, Eriko; Kimura, Fukiko; Miyajima, Kumiko; Shigeto, Hajime

2017-10-21

A new single-cell microarray chip was designed and developed to separate and analyze single adherent and non-adherent cancer cells. The single-cell microarray chip is made of polystyrene with over 60,000 microchambers of 10 different size patterns (31-40 µm upper diameter, 11-20 µm lower diameter). A drop of suspension of adherent carcinoma (NCI-H1650) and non-adherent leukocyte (CCRF-CEM) cells was placed onto the chip, and single-cell occupancy of NCI-H1650 and CCRF-CEM was determined to be 79% and 84%, respectively. This was achieved by controlling the chip design and surface treatment. Analysis of protein expression in single NCI-H1650 and CCRF-CEM cells was performed on the single-cell microarray chip by multi-antibody staining. Additionally, with this system, we retrieved positive single cells from the microchambers by a micromanipulator. Thus, this system demonstrates the potential for easy and accurate separation and analysis of various types of single cells.

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarrays. 22-24 January 2001, Zurich, Switzerland.

PubMed

Jain, K K

2001-02-01

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarray technology covered the latest advances in this technology and applications in life sciences. Highlights of the meetings are reported briefly with emphasis on applications in genomics, drug discovery and molecular diagnostics. There was an emphasis on microfluidics because of the wide applications in laboratory and drug discovery. The lab-on-a-chip provides the facilities of a complete laboratory in a hand-held miniature device. Several microarray systems have been used for hybridisation and detection techniques. Oligonucleotide scanning arrays provide a versatile tool for the analysis of nucleic acid interactions and provide a platform for improving the array-based methods for investigation of antisense therapeutics. A method for analysing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional scanner has considerable potential in molecular diagnostics. Various applications of microarray technology for high-throughput screening in drug discovery and single nucleotide polymorphisms (SNP) analysis were discussed. Protein chips have important applications in proteomics. With the considerable amount of data generated by the different technologies using microarrays, it is obvious that the reading of the information and its interpretation and management through the use of bioinformatics is essential. Various techniques for data analysis were presented. Biochip and microarray technology has an essential role to play in the evolving trends in healthcare, which integrate diagnosis with prevention/treatment and emphasise personalised medicines.

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.

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.

AFM 4.0: a toolbox for DNA microarray analysis

PubMed Central

Breitkreutz, Bobby-Joe; Jorgensen, Paul; Breitkreutz, Ashton; Tyers, Mike

2001-01-01

We have developed a series of programs, collectively packaged as Array File Maker 4.0 (AFM), that manipulate and manage DNA microarray data. AFM 4.0 is simple to use, applicable to any organism or microarray, and operates within the familiar confines of Microsoft Excel. Given a database of expression ratios, AFM 4.0 generates input files for clustering, helps prepare colored figures and Venn diagrams, and can uncover aneuploidy in yeast microarray data. AFM 4.0 should be especially useful to laboratories that do not have access to specialized commercial or in-house software. PMID:11532221

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

PubMed

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

2014-01-01

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

Gray Matter Heterotopia, Mental Retardation, Developmental Delay, Microcephaly, and Facial Dysmorphisms in a Boy with Ring Chromosome 6: A 10-Year Follow-Up and Literature Review.

PubMed

Liu, Shu; Wang, Zhiqing; Wei, Sisi; Liang, Jinqun; Chen, Nuan; OuYang, Haimei; Zeng, Weihong; Chen, Liying; Xie, Xunjie; Jiang, Jianhui

2018-04-14

Ring chromosome 6, r(6), is an extremely rare cytogenetic abnormality with clinical heterogeneity which arises typically de novo. The phenotypes of r(6) can be highly variable, ranging from almost normal to severe malformations and neurological defects. Up to now, only 33 cases have been reported in the literature. In this 10-year follow-up study, we report a case presenting distinctive facial features, severe developmental delay, and gray matter heterotopia with r(6) and terminal deletions of 6p25.3 (115426-384174, 268 kb) and 6q26-27 (168697778-170732033, 2.03 Mb) encompassing 2 and 15 candidate genes, respectively, which were detected using G-banding karyotyping, FISH, and chromosomal microarray analysis. We also analyzed the available information on the clinical features of the reported r(6) cases in order to provide more valuable information on genotype-phenotype correlations. To the best of our knowledge, this is the first report of gray matter heterotopia manifested in a patient with r(6) in China, and the deletions of 6p and 6q in our case are the smallest with the precise size of euchromatic material loss currently known. © 2018 S. Karger AG, Basel.

Simultaneous Downregulation of MTHFR and COMT in Switchgrass Affects Plant Performance and Induces Lesion-Mimic Cell Death.

PubMed

Liu, Sijia; Fu, Chunxiang; Gou, Jiqing; Sun, Liang; Huhman, David; Zhang, Yunwei; Wang, Zeng-Yu

2017-01-01

Switchgrass ( Panicum virgatum ) has been developed into a model lignocellulosic bioenergy crop. Downregulation of caffeic acid O -methyltransferase (COMT), a key enzyme in lignin biosynthesis, has been shown to alter lignification and increase biofuel yield in switchgrass. Methylenetetrahydrofolate reductase (MTHFR) mediates C1 metabolism and provides methyl units consumed by COMT. It was predicted that co-silencing of MTHFR and COMT would impact lignification even more than either of the single genes. However, our results showed that strong downregulation of MTHFR in a COMT -deficient background led to altered plant growth and development, but no significant change in lignin content or composition was found when compared with COMT plants. Another unexpected finding was that the double MTHFR/COMT downregulated plants showed a novel lesion-mimic leaf phenotype. Molecular analyses revealed that the lesion-mimic phenotype was caused by the synergistic effect of MTHFR and COMT genes, with MTHFR playing a predominant role. Microarray analysis showed significant induction of genes related to oxidative and defense responses. The results demonstrated the lack of additive effects of MTHFR and COMT on lignification. Furthermore, this research revealed an unexpected role of the two genes in the modulation of lesion-mimic cell death as well as their synergistic effects on agronomic performance.

Simultaneous Downregulation of MTHFR and COMT in Switchgrass Affects Plant Performance and Induces Lesion-Mimic Cell Death

PubMed Central

Liu, Sijia; Fu, Chunxiang; Gou, Jiqing; Sun, Liang; Huhman, David; Zhang, Yunwei; Wang, Zeng-Yu

2017-01-01

Switchgrass (Panicum virgatum) has been developed into a model lignocellulosic bioenergy crop. Downregulation of caffeic acid O-methyltransferase (COMT), a key enzyme in lignin biosynthesis, has been shown to alter lignification and increase biofuel yield in switchgrass. Methylenetetrahydrofolate reductase (MTHFR) mediates C1 metabolism and provides methyl units consumed by COMT. It was predicted that co-silencing of MTHFR and COMT would impact lignification even more than either of the single genes. However, our results showed that strong downregulation of MTHFR in a COMT-deficient background led to altered plant growth and development, but no significant change in lignin content or composition was found when compared with COMT plants. Another unexpected finding was that the double MTHFR/COMT downregulated plants showed a novel lesion-mimic leaf phenotype. Molecular analyses revealed that the lesion-mimic phenotype was caused by the synergistic effect of MTHFR and COMT genes, with MTHFR playing a predominant role. Microarray analysis showed significant induction of genes related to oxidative and defense responses. The results demonstrated the lack of additive effects of MTHFR and COMT on lignification. Furthermore, this research revealed an unexpected role of the two genes in the modulation of lesion-mimic cell death as well as their synergistic effects on agronomic performance. PMID:28676804

The Identification of Microdeletion and Reciprocal Microduplication in 22q11.2 Using High-Resolution CMA Technology

PubMed Central

Leite, Ana Julia Cunha; Pinto, Irene Plaza; Cunha, Damiana Mirian da Cruz e; Ribeiro, Cristiano Luiz; da Silva, Claudio Carlos; da Cruz, Aparecido Divino; Minasi, Lysa Bernardes

2016-01-01

The chromosome 22q11.2 region has long been implicated in genomic diseases. Some genomic regions exhibit numerous low copy repeats with high identity in which they provide increased genomic instability and mediate deletions and duplications in many disorders. DiGeorge Syndrome is the most common deletion syndrome and reciprocal duplications could be occurring in half of the frequency of microdeletions. We described five patients with phenotypic variability that carries deletions or reciprocal duplications at 22q11.2 detected by Chromosomal Microarray Analysis. The CytoScan HD technology was used to detect changes in the genome copy number variation of patients who had clinical indication to global developmental delay and a normal karyotype. We observed in our study three microdeletions and two microduplications in 22q11.2 region with variable intervals containing known genes and unstudied transcripts as well as the LCRs that are often flanking and within this genomic rearrangement. The identification of these variants is of particular interest because it may provide insight into genes or genomic regions that are crucial for specific phenotypic manifestations and are useful to assist in the quest for understanding the mechanisms subjacent to genomic deletions and duplications. PMID:27123452

An in vivo model of epithelial to mesenchymal transition reveals a mitogenic switch

PubMed Central

Jahn, Stephan C.; Law, Mary E.; Corsino, Patrick E.; Parker, Nicole N.; Pham, Kien; Davis, Bradley J.; Lu, Jianrong; Law, Brian K.

2012-01-01

The epithelial to mesenchymal transition (EMT) is a process by which differentiated epithelial cells transition to a mesenchymal phenotype. EMT enables the escape of epithelial cells from the rigid structural constraints of the tissue architecture to a phenotype more amenable to cell migration and, therefore, invasion and metastasis. We characterized an in vivo model of EMT and discovered that marked changes in mitogenic signaling occurred during this process. DNA microarray analysis revealed that the expression of a number of genes varied significantly between post-EMT and pre-EMT breast cancer cells. Post-EMT cancer cells upregulated mRNA encoding c-Met and the PDGF and LPA receptors, and acquired increased responsiveness to HGF, PDGF, and LPA. This rendered the post-EMT cells responsive to the growth inhibitory effects of HGF, PDGF, and LPA receptor inhibitors/antagonists. Furthermore, post- EMT cells exhibited decreased basal Raf and Erk phosphorylation, and in comparison to pre-EMT cells, their proliferation was poorly inhibited by a MEK inhibitor. These studies suggest that therapies need to be designed to target both pre-EMT and post-EMT cancer cells and that signaling changes in post- EMT cells may allow them to take advantage of paracrine signaling from the stroma in vivo. PMID:22906417

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.

Differential gene expression profiling of human adipose stem cells differentiating into smooth muscle-like cells by TGFβ1/BMP4

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

Elçin, Ayşe Eser; Parmaksiz, Mahmut; Dogan, Arin

Regenerative repair of the vascular system is challenging from the perspectives of translational medicine and tissue engineering. There are fundamental hurdles in front of creating bioartificial arteries, which involve recaputilation of the three-layered structure under laboratory settings. Obtaining and maintaining smooth muscle characteristics is an important limitation, as the transdifferentiated cells fail to display mature phenotype. This study aims to shed light on the smooth muscle differentiation of human adipose stem cells (hASCs). To this end, we first acquired hASCs from lipoaspirate samples. Upon characterization, the cells were induced to differentiate into smooth muscle (SM)-like cells using a variety ofmore » inducer combinations. Among all, TGFβ1/BMP4 combination had the highest differentiation efficiency, based on immunohistochemical analyses. hSM-like cell samples were compared to hASCs and to the positive control, human coronary artery-smooth muscle cells (hCA-SMCs) through gene transcription profiling. Microarray findings revealed the activation of gene groups that function in smooth muscle differentiation, signaling pathways, extracellular modeling and cell proliferation. Our results underline the effectiveness of the growth factors and suggest some potential variables for detecting the SM-like cell characteristics. Evidence in transcriptome level was used to evaluate the TGFβ1/BMP4 combination as a previously unexplored effector for the smooth muscle differentiation of adipose stem cells. - Highlights: • Human adipose stem cells (hASCs) were isolated, characterized and cultured. • Growth factor combinations were evaluated for their effectiveness in differentiation using IHC. • hASCs were differentiated into smooth muscle (SM)-like cells using TGF-β1 and BMP4 combination. • Microarray analysis was performed for hASCs, SM-like cells and coronary artery-SMCs. • Microarray data was used to perform hierarchical clustering and interpretation of activated pathways.« less

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 ...

Where statistics and molecular microarray experiments biology meet.

PubMed

Kelmansky, Diana M

2013-01-01

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

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

Novel calibration tools and validation concepts for microarray-based platforms used in molecular diagnostics and food safety control.

PubMed

Brunner, C; Hoffmann, K; Thiele, T; Schedler, U; Jehle, H; Resch-Genger, U

2015-04-01

Commercial platforms consisting of ready-to-use microarrays printed with target-specific DNA probes, a microarray scanner, and software for data analysis are available for different applications in medical diagnostics and food analysis, detecting, e.g., viral and bacteriological DNA sequences. The transfer of these tools from basic research to routine analysis, their broad acceptance in regulated areas, and their use in medical practice requires suitable calibration tools for regular control of instrument performance in addition to internal assay controls. Here, we present the development of a novel assay-adapted calibration slide for a commercialized DNA-based assay platform, consisting of precisely arranged fluorescent areas of various intensities obtained by incorporating different concentrations of a "green" dye and a "red" dye in a polymer matrix. These dyes present "Cy3" and "Cy5" analogues with improved photostability, chosen based upon their spectroscopic properties closely matching those of common labels for the green and red channel of microarray scanners. This simple tool allows to efficiently and regularly assess and control the performance of the microarray scanner provided with the biochip platform and to compare different scanners. It will be eventually used as fluorescence intensity scale for referencing of assays results and to enhance the overall comparability of diagnostic tests.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

Transcriptional master regulator analysis in breast cancer genetic networks.

PubMed

Tovar, Hugo; García-Herrera, Rodrigo; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

2015-12-01

Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Novel mutations in CRB1 and ABCA4 genes cause Leber congenital amaurosis and Stargardt disease in a Swedish family

PubMed Central

Jonsson, Frida; Burstedt, Marie S; Sandgren, Ola; Norberg, Anna; Golovleva, Irina

2013-01-01

This study aimed to identify genetic mechanisms underlying severe retinal degeneration in one large family from northern Sweden, members of which presented with early-onset autosomal recessive retinitis pigmentosa and juvenile macular dystrophy. The clinical records of affected family members were analysed retrospectively and ophthalmological and electrophysiological examinations were performed in selected cases. Mutation screening was initially performed with microarrays, interrogating known mutations in the genes associated with recessive retinitis pigmentosa, Leber congenital amaurosis and Stargardt disease. Searching for homozygous regions with putative causative disease genes was done by high-density SNP-array genotyping, followed by segregation analysis of the family members. Two distinct phenotypes of retinal dystrophy, Leber congenital amaurosis and Stargardt disease were present in the family. In the family, four patients with Leber congenital amaurosis were homozygous for a novel c.2557C>T (p.Q853X) mutation in the CRB1 gene, while of two cases with Stargardt disease, one was homozygous for c.5461-10T>C in the ABCA4 gene and another was carrier of the same mutation and a novel ABCA4 mutation c.4773+3A>G. Sequence analysis of the entire ABCA4 gene in patients with Stargardt disease revealed complex alleles with additional sequence variants, which were evaluated by bioinformatics tools. In conclusion, presence of different genetic mechanisms resulting in variable phenotype within the family is not rare and can challenge molecular geneticists, ophthalmologists and genetic counsellors. PMID:23443024

Dopaminergic dysregulation in mice selectively bred for excessive exercise or obesity.

PubMed

Mathes, Wendy Foulds; Nehrenberg, Derrick L; Gordon, Ryan; Hua, Kunjie; Garland, Theodore; Pomp, Daniel

2010-07-11

Dysregulation of the dopamine system is linked to various aberrant behaviors, including addiction, compulsive exercise, and hyperphagia leading to obesity. The goal of the present experiments was to determine how dopamine contributes to the expression of opposing phenotypes, excessive exercise and obesity. We hypothesized that similar alterations in dopamine and dopamine-related gene expression may underly obesity and excessive exercise, as competing traits for central reward pathways. Moreover, we hypothesized that selective breeding for high levels of exercise or obesity may have influenced genetic variation controlling these pathways, manifesting as opposing complex traits. Dopamine, dopamine-related peptide concentrations, and gene expression were evaluated in dorsal striatum (DS) and nucleus accumbens (NA) of mice from lines selectively bred for high rates of wheel running (HR) or obesity (M16), and the non-selected ICR strain from which these lines were derived. HPLC analysis showed significantly greater neurotransmitter concentrations in DS and NA of HR mice compared to M16 and ICR. Microarray analysis showed significant gene expression differences between HR and M16 compared to ICR in both brain areas, with changes revealed throughout the dopamine pathway including D1 and D2 receptors, associated G-proteins (e.g., Golf), and adenylate cyclase (e.g., Adcy5). The results suggest that similar modifications within the dopamine system may contribute to the expression of opposite phenotypes in mice, demonstrating that alterations within central reward pathways can contribute to both obesity and excessive exercise. Copyright 2010 Elsevier B.V. All rights reserved.

Dopaminergic Dysregulation in Mice Selectively Bred for Excessive Exercise or Obesity

PubMed Central

Nehrenberg, Derrick L.; Gordon, Ryan; Hua, Kunjie; Garland, Theodore; Pomp, Daniel

2010-01-01

Dysregulation of the dopamine system is linked to various aberrant behaviors, including addiction, compulsive exercise, and hyperphagia leading to obesity. The goal of the present experiments was to determine how dopamine contributes to the expression of opposing phenotypes, excessive exercise and obesity. We hypothesized that similar alterations in dopamine and dopamine-related gene expression may underly obesity and excessive exercise, as competing traits for central reward pathways. Moreover, we hypothesized that selective breeding for high levels of exercise or obesity may have influenced genetic variation controlling these pathways, manifesting as opposing complex traits. Dopamine, dopamine-related peptide concentrations, and gene expression were evaluated in dorsal striatum (DS) and nucleus accumbens (NA) of mice from lines selectively bred for high rates of wheel running (HR) or obesity (M16), and the non-selected ICR strain from which these lines were derived. HPLC analysis showed significantly greater neurotransmitter concentrations in DS and NA of HR mice compared to M16 and ICR. Microarray analysis showed significant gene expression differences between HR and M16 compared to ICR in both brain areas, with changes revealed throughout the dopamine pathway including D1 and D2 receptors, associated G-proteins (eg. Golf), and adenylate cyclase (eg. Adcy5). The results suggest similar modifications within the dopamine system may contribute to the expression of opposite phenotypes in mice, demonstrating that alterations within central reward pathways can contribute to both obesity and excessive exercise. PMID:20156488

Establishment of a recessive mutant small-eye rat with lens involution and retinal detachment associated with partial deletion and rearrangement of the Cryba1 gene.

PubMed

Yamada, Toshiyuki; Nanashima, Naoki; Shimizu, Takeshi; Nakazawa, Yosuke; Nakazawa, Mitsuru; Tsuchida, Shigeki

2015-10-15

From our stock of SDRs (Sprague-Dawley rats), we established a mutant strain having small opaque eyes and named it HiSER (Hirosaki small-eye rat). The HiSER phenotype is progressive and autosomal recessive. In HiSER eyes, disruption and involution of the lens, thickening of the inner nuclear layer, detachment and aggregation of the retina, rudimentary muscle in the ciliary body and cell infiltration in the vitreous humour were observed. Genetic linkage analysis using crossing with Brown Norway rat suggested that the causative gene(s) is located on chromosome 10. Microarray analysis showed that the expression level of the Cryba1 gene encoding βA3/A1-crystallin on chromosome 10 was markedly decreased in HiSER eyes. Genomic PCR revealed deletion of a 3.6-kb DNA region encompassing exons 4-6 of the gene in HiSERs. In HiSER eyes, a chimaeric transcript of the gene containing exons 1-3 and an approximately 250-bp sequence originating from the 3'-UTR of the Nufip2 gene, located downstream of the breakpoint in the opposite direction, was present. Whereas the chimaeric transcript was expressed in HiSER eyes, neither normal nor chimaeric βA3/A1-crystallin proteins were detected by Western blot analysis. Real-time RT (reverse transcription)-PCR analysis revealed that expression level of the Nufip2 gene in the HiSER eye was 40% of that in the SDR eye. These results suggest that the disappearance of the βA3/A1-crystallin protein and, in addition, down-regulation of the Nufip2 gene as a consequence of gene rearrangement causes the HiSER phenotype. © 2015 Authors; published by Portland Press Limited.

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

ERIC Educational Resources Information Center

McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

2012-01-01

Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

A MICROARRAY ANALYSIS OF GENE EXPRESSION IN THE EMBRYONIC FORELIMB OF THE C57BL/6J MOUSE REVEALS SIGNIFICANT ALTERATIONS METABOLIC AND DEVELOPMENTAL REGULATION FOLLOWING ETHANOL EXPOSURE.

EPA Science Inventory

The observation of transcriptional changes following embryonic ethanol exposure may provide significant insights into the biological response to ethanol exposure. In this study, we used microarray analysis to examine the transcriptional response of the developing limb to a dose ...

Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP)

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

Ovacik, Meric A.; Sen, Banalata; Euling, Susan Y.

Pathway activity level analysis, the approach pursued in this study, focuses on all genes that are known to be members of metabolic and signaling pathways as defined by the KEGG database. The pathway activity level analysis entails singular value decomposition (SVD) of the expression data of the genes constituting a given pathway. We explore an extension of the pathway activity methodology for application to time-course microarray data. We show that pathway analysis enhances our ability to detect biologically relevant changes in pathway activity using synthetic data. As a case study, we apply the pathway activity level formulation coupled with significancemore » analysis to microarray data from two different rat testes exposed in utero to Dibutyl Phthalate (DBP). In utero DBP exposure in the rat results in developmental toxicity of a number of male reproductive organs, including the testes. One well-characterized mode of action for DBP and the male reproductive developmental effects is the repression of expression of genes involved in cholesterol transport, steroid biosynthesis and testosterone synthesis that lead to a decreased fetal testicular testosterone. Previous analyses of DBP testes microarray data focused on either individual gene expression changes or changes in the expression of specific genes that are hypothesized, or known, to be important in testicular development and testosterone synthesis. However, a pathway analysis may inform whether there are additional affected pathways that could inform additional modes of action linked to DBP developmental toxicity. We show that Pathway activity analysis may be considered for a more comprehensive analysis of microarray data.« less

Biomarkers of acute respiratory allergen exposure: Screening for sensitization potential

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

Pucheu-Haston, Cherie M., E-mail: Pucheu-Haston.Cherie@epa.go; Copeland, Lisa B.; Vallanat, Beena

2010-04-15

Effective hazard screening will require the development of high-throughput or in vitro assays for the identification of potential sensitizers. The goal of this preliminary study was to identify potential biomarkers that differentiate the response to allergens vs non-allergens following an acute exposure in naive individuals. Female BALB/c mice received a single intratracheal aspiration exposure to Metarhizium anisopliae crude antigen (MACA) or bovine serum albumin (BSA) in Hank's Balanced Salt Solution (HBSS) or HBSS alone. Mice were terminated after 1, 3, 6, 12, 18 and 24 h. Bronchoalveolar lavage fluid (BALF) was evaluated to determine total and differential cellularity, total proteinmore » concentration and LDH activity. RNA was isolated from lung tissue for microarray analysis and qRT-PCR. MACA administration induced a rapid increase in BALF neutrophils, lymphocytes, eosinophils and total protein compared to BSA or HBSS. Microarray analysis demonstrated differential expression of genes involved in cytokine production, signaling, inflammatory cell recruitment, adhesion and activation in 3 and 12 h MACA-treated samples compared to BSA or HBSS. Further analyses allowed identification of approx 100 candidate biomarker genes. Eleven genes were selected for further assessment by qRT-PCR. Of these, 6 demonstrated persistently increased expression (Ccl17, Ccl22, Ccl7, Cxcl10, Cxcl2, Saa1), while C3ar1 increased from 6-24 h. In conclusion, a single respiratory exposure of mice to an allergenic mold extract induces an inflammatory response which is distinct in phenotype and gene transcription from the response to a control protein. Further validation of these biomarkers with additional allergens and irritants is needed. These biomarkers may facilitate improvements in screening methods.« less

Microarray analysis of gene expression patterns of high lycopene tomato generated from seeds after long-term space flight

NASA Astrophysics Data System (ADS)

Lu, Jinying; Ren, Chunxiao; Pan, Yi; Nechitailo, Galina S.; Liu, Min

Lycopene content is a most vital trait of tomatoes due to the role of lycopene in reducing the risk of some kinds of cancers. In this experiment, we gained a high lycopene (hl) tomato (named HY-2), after seven generations of self-cross selection, from seeds Russian MNP-1 carried in Russia MIR space station for six years. HPLC result showed that the lycopene content was 1.6 times more than that in Russian MNP-1 (the wild type). Microarray analysis presented the general profile of differential expressed genes at the tomato developmental stage of 7DPB (days post breaker). One hundred and forty three differential expression genes were identified according to the following criterion: the average changes were no less than 1.5 folds with q-value (similar to FDR) less than 0.05 or changes were no less than 1.5 folds in all three biological replications. Most of the differential expressed genes were mainly involved in metabolism, response to stimulus, biosynthesis, development and regulation. Particularly, we discussed the genes involved in protein metabolism, response to unfolded protein, carotenoid biosynthesis and photosynthesis that might be related to the fruit development and the accumulation of lycopene. What's more, we conducted QRT-PCR validation of five key genes (Fps, CrtL-b, CrtR-b, Zep and Nxs) in the lycopene biosynthesis pathway through time courses and that provided the direct molecular evidence for the hl phenotype. Our results demonstrate that long-term space flight, as a rarely used tool, can positively cause some beneficial mutations in the seeds and thus to help to generate a high quality variety, combined with ground selections.

Familial Xp22.33-Xp22.12 deletion delineated by chromosomal microarray analysis causes proportionate short stature.

PubMed

Cho, Sung Yoon; Ki, Chang-Seok; Jang, Ja-Hyun; Sohn, Young Bae; Park, Sung Won; Kim, Se Hwa; Kim, Su Jin; Jin, Dong-Kyu

2012-06-01

Patients with Xp deletions have short stature and may have some somatic traits typical of Turner syndrome (TS), whereas gonadal function is generally preserved. In most studies of these patients, microsatellites have been used to determine the break point of the Xp deletion. In the present study, we describe the clinical, cytogenetic, and chromosomal microarray (CMA) analysis of a family with an Xp22.33-Xp22.12 deletion. Two female siblings, aged 8 years 9 months and 11 years 10 months, presented with short stature. The older sibling's height (index case) was 137.9 cm (-1.81 SDS) and the younger sibling's height was 118.6 cm (-2.13 SDS). The mother and both daughters had only a short stature; a skeletal survey showed normal findings except for mildly shortened 4th and 5th metacarpal bones. No features of TS were present. The deletion appeared terminal with a breakpoint within Xp22.2 located about 19.9 Mb from the Xp telomere. The deletion contained 102 protein-coding genes. A probe of the end breakage point was located at the 19,908,986th base of the X chromosome, and a probe of the marginal normal region near the breakage point was located at the 19,910,848th base of the X chromosome. Therefore, the breakage point was concluded to be located between these two probes. In summary, we report a familial case of an Xp deletion. The findings of our study may be helpful in further analyzing the phenotypes associated with Xp deletions. Copyright © 2012 Wiley Periodicals, Inc.

An XRCC4 Splice Mutation Associated With Severe Short Stature, Gonadal Failure, and Early-Onset Metabolic Syndrome

PubMed Central

de Bruin, Christiaan; Mericq, Verónica; Andrew, Shayne F.; van Duyvenvoorde, Hermine A.; Verkaik, Nicole S.; Losekoot, Monique; Porollo, Aleksey; Garcia, Hernán; Kuang, Yi; Hanson, Dan; Clayton, Peter; van Gent, Dik C.; Wit, Jan M.; Hwa, Vivian

2015-01-01

Context: Severe short stature can be caused by defects in numerous biological processes including defects in IGF-1 signaling, centromere function, cell cycle control, and DNA damage repair. Many syndromic causes of short stature are associated with medical comorbidities including hypogonadism and microcephaly. Objective: To identify an underlying genetic etiology in two siblings with severe short stature and gonadal failure. Design: Clinical phenotyping, genetic analysis, complemented by in vitro functional studies of the candidate gene. Setting: An academic pediatric endocrinology clinic. Patients or Other Participants: Two adult siblings (male patient [P1] and female patient 2 [P2]) presented with a history of severe postnatal growth failure (adult heights: P1, −6.8 SD score; P2, −4 SD score), microcephaly, primary gonadal failure, and early-onset metabolic syndrome in late adolescence. In addition, P2 developed a malignant gastrointestinal stromal tumor at age 28. Intervention(s): Single nucleotide polymorphism microarray and exome sequencing. Results: Combined microarray analysis and whole exome sequencing of the two affected siblings and one unaffected sister identified a homozygous variant in XRCC4 as the probable candidate variant. Sanger sequencing and mRNA studies revealed a splice variant resulting in an in-frame deletion of 23 amino acids. Primary fibroblasts (P1) showed a DNA damage repair defect. Conclusions: In this study we have identified a novel pathogenic variant in XRCC4, a gene that plays a critical role in non-homologous end-joining DNA repair. This finding expands the spectrum of DNA damage repair syndromes to include XRCC4 deficiency causing severe postnatal growth failure, microcephaly, gonadal failure, metabolic syndrome, and possibly tumor predisposition. PMID:25742519

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Analyzing gene perturbation screens with nested effects models in R and bioconductor.

PubMed

Fröhlich, Holger; Beissbarth, Tim; Tresch, Achim; Kostka, Dennis; Jacob, Juby; Spang, Rainer; Markowetz, F

2008-11-01

Nested effects models (NEMs) are a class of probabilistic models introduced to analyze the effects of gene perturbation screens visible in high-dimensional phenotypes like microarrays or cell morphology. NEMs reverse engineer upstream/downstream relations of cellular signaling cascades. NEMs take as input a set of candidate pathway genes and phenotypic profiles of perturbing these genes. NEMs return a pathway structure explaining the observed perturbation effects. Here, we describe the package nem, an open-source software to efficiently infer NEMs from data. Our software implements several search algorithms for model fitting and is applicable to a wide range of different data types and representations. The methods we present summarize the current state-of-the-art in NEMs. Our software is written in the R language and freely avail-able via the Bioconductor project at http://www.bioconductor.org.

Carbapenemase-producing Enterobacteriaceae: a 2-year surveillance in a hospital in Iaşi, Romania.

PubMed

Braun, Sascha D; Dorneanu, Olivia S; Vremeră, Teodora; Reißig, Annett; Monecke, Stefan; Ehricht, Ralf

2016-01-01

Limited information is currently available about the prevalence of carbapenemase-producing Enterobacteriaceae (CPE) in Romania. Routine tests of 1,993 clinical isolates at a hospital in Iaşi yielded 46 isolates that were resistant to carbapenems. All 46 isolates were phenotypically and genotypically analyzed using VITEK-2 and DNA microarray-based assays. Isolates were assigned to Klebsiella pneumoniae and Enterobacter cloacae. For 39 isolates, carbapenem resistance was confirmed and 37 harbored at least one carbapenem resistance gene. Two isolates were probably resistant due to AmpC β-lactamases in combination with a porin loss. The overall concordance between detected phenotype and genotype was 95%. Our data show that carbapenemase-producing isolates with different underlying resistance mechanisms are still rare in Iaşi, but the global rise of CPE warrants intensified surveillance.

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

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.

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.

The Effect of Estradiol-17(beta), Goitrogen (T3), and Flutamide on Gene Expression in Medaka, Oryzias latipes

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

E.Haut, J

Concern has been generated over the discovery of endocrine disrupting chemicals in rivers near sewage outflows. The presence of endocrine disrupting chemicals such as estradiol-17{beta} has been associated with a reduction of reproductive success in fish and an increase in the female phenotype and gonadal intersex in fish downstream of sewage treatment facilities. Such effects are believed to result from a disruption in the normal estrogenic pathways since estrogen plays a vital role in reproduction, sexual differentiation, the developments of secondary sex characteristics, and ovulation. Most studies have focused on the effect of a single endocrine disruptor on a singlemore » gene which does not provide for the interaction between genes. Microarray technology has made it possible to put an entire genome on a single chip so that researchers can get a clearer picture of the interaction of genes expressed in a cell and changes of said interactions when those cells are exposed to various conditions. Medaka males were exposed to known endocrine disruptors, estradial-17{beta} and goitrogen, and medaka females were exposed to flutamide. All treatments were then compared to controls. Total RNA was extracted from the livers of both treated and untreated males and hybridized to a microarray chip designed to have EST sequences specific to medaka. ESTs were identified through two-channel microarray analysis and compared to GenBank using blastn searches to identify up regulated genes. Choriogenins H and L, zona radiata, and vitellogenin, previously shown to be estrogen-induced in male fish were identified. Heat shock proteins (hsp70, hsp90, and hsp8) were also induced by estradiol-17{beta}, as was choriogenin Hminor. Exposure to goitrogen (T3) resulted in the induced expression of glutathione S-transferase and a GABA receptor protein in male medaka. Treatment with flutamide, an antiandrogen, caused the up regulation of choriogenin L, choriogenin Hminor, and zona radiata-2 in female medaka. Further study of the genes identified in this study may serve as possible biomarkers to signal the effects caused by the presence of endocrine disruptors and provide a screening mechanism for the presence of estrogens in the environment. Microarray technology may provide a means to screen multiple biomarkers simultaneously and provide a more rapid and accurate tool for assessing endocrine disruption due to environmental pollutants.« less

Doxycycline affects gene expression profiles in aortic tissues in a rat model of vascular calcification.

PubMed

Lu, Hailin; Jiang, Wenhong; Yang, Han; Qin, Zhong; Guo, Si-En; Hu, Ming; Qin, Xiao

2017-11-01

Vitamin D 3 -induced vascular calcification (VC) in rats shares many phenotypical similarities with calcification occurring in human atherosclerosis, diabetes mellitus and chronic kidney disease, thereby it is a reliable model for identifying chemopreventive agents. Doxycycline has been shown to effectively attenuated VC. This study aimed to explore the effects of doxycycline on gene expression profiles in VC rats. The model of VC in rats was established by subcutaneous injection of vitamin D3 for 3days. Doxycycline at 120mgkg -1 day -1 was given via subcutaneous injection for 14days. Rat pathological changes, calcium deposition and calcium content in aortic tissues were measured by Hematoxylin-eosin, von Kossa staining and colorimetry, respectively. The gene change profile of aortic tissues after doxycycline treatment was assessed by Gene Microarray analysis using the Agilent Whole Rat Genome Oligo Microarray. The results showed that doxycycline significantly decreased the deposition of calcium, reduced the relative calcification area and alleviated pathological injury in aortic tissues. In addition, doxycycline treatment altered 88 gene expressions compared with untreated VD group. Of these, 61 genes were down-regulated and 27 genes were up-regulated. The functions of differentially expressed (DE) genes were involved in neutrophil chemotaxis, chronic inflammatory response, negative regulation of apoptotic process, cellular response to mechanical stimulus and immune response, etc. In conclusions, this study might provide the potential novel insights into the molecular mechanisms of doxycycline on VC. Copyright © 2017. Published by Elsevier Inc.

Wild-type APC predicts poor prognosis in microsatellite-stable proximal colon cancer.

PubMed

Jorissen, Robert N; Christie, Michael; Mouradov, Dmitri; Sakthianandeswaren, Anuratha; Li, Shan; Love, Christopher; Xu, Zheng-Zhou; Molloy, Peter L; Jones, Ian T; McLaughlin, Stephen; Ward, Robyn L; Hawkins, Nicholas J; Ruszkiewicz, Andrew R; Moore, James; Burgess, Antony W; Busam, Dana; Zhao, Qi; Strausberg, Robert L; Lipton, Lara; Desai, Jayesh; Gibbs, Peter; Sieber, Oliver M

2015-09-15

APC mutations (APC-mt) occur in ∼70% of colorectal cancers (CRCs), but their relationship to prognosis is unclear. APC prognostic value was evaluated in 746 stage I-IV CRC patients, stratifying for tumour location and microsatellite instability (MSI). Microarrays were used to identify a gene signature that could classify APC mutation status, and classifier ability to predict prognosis was examined in an independent cohort. Wild-type APC microsatellite stable (APC-wt/MSS) tumours from the proximal colon showed poorer overall and recurrence-free survival (OS, RFS) than APC-mt/MSS proximal, APC-wt/MSS distal and APC-mt/MSS distal tumours (OS HR⩾1.79, P⩽0.015; RFS HR⩾1.88, P⩽0.026). APC was a stronger prognostic indicator than BRAF, KRAS, PIK3CA, TP53, CpG island methylator phenotype or chromosomal instability status (P⩽0.036). Microarray analysis similarly revealed poorer survival in MSS proximal cancers with an APC-wt-like signature (P=0.019). APC status did not affect outcomes in MSI tumours. In a validation on 206 patients with proximal colon cancer, APC-wt-like signature MSS cases showed poorer survival than APC-mt-like signature MSS or MSI cases (OS HR⩾2.50, P⩽0.010; RFS HR⩾2.14, P⩽0.025). Poor prognosis APC-wt/MSS proximal tumours exhibited features of the sessile serrated neoplasia pathway (P⩽0.016). APC-wt status is a marker of poor prognosis in MSS proximal colon cancer.

Francisella tularensis alters human neutrophil gene expression: insights into the molecular basis of delayed neutrophil apoptosis

PubMed Central

Schwartz, Justin T.; Bandyopadhyay, Sarmistha; Kobayashi, Scott D.; McCracken, Jenna; Whitney, Adeline R.; DeLeo, Frank R.; Allen, Lee-Ann H.

2013-01-01

We demonstrated recently that Francisella tularensis profoundly impairs human neutrophil apoptosis, but how this is achieved is largely unknown. Herein we used human oligonucleotide microarrays to test the hypothesis that changes in neutrophil gene expression contribute to this phenotype, and now demonstrate that F. tularensis live vaccine strain (LVS) caused significant changes in neutrophil gene expression over a 24 h time period relative to the uninfected controls. Of ~47,000 genes analyzed, 3,435 were significantly up- or down-regulated by LVS, including 365 unique genes associated with apoptosis and cell survival. Specific targets in this category included genes associated with the intrinsic and extrinsic apoptotic pathways (CFLAR, TNFAIP3, TNFRSF10D, SOD2, BCL2A1, BIRC4, PIM2, TNFSF10, TNFRSF10C, CASP2, and CASP8) and genes that act via the NF B pathway and other mechanisms to prolong cell viability (NFKB1, NFKB2, and RELA, IL1B, CAST, CDK2, GADD45B, BCL3, BIRC3, CDK2, IL1A, PBEF1, IL6, CXCL1, CCL4 and VEGF). The microarray data were confirmed by qPCR and pathway analysis. Moreover, we demonstrate that X-linked inhibitor of apoptosis (XIAP) protein remained abundant in PMNs over 48 h of LVS infection, whereas BAX mRNA and protein were progressively down-regulated. These data strongly suggest that antiapoptotic and pro-survival mechanisms collaborate to sustain the viability of F. tularensis infected neutrophils. PMID:22986450

Global transcriptional profiling reveals similarities and differences between human stem cell-derived cardiomyocyte clusters and heart tissue.

PubMed

Synnergren, Jane; Améen, Caroline; Jansson, Andreas; Sartipy, Peter

2012-02-27

It is now well documented that human embryonic stem cells (hESCs) can differentiate into functional cardiomyocytes. These cells constitute a promising source of material for use in drug development, toxicity testing, and regenerative medicine. To assess their utility as replacement or complement to existing models, extensive phenotypic characterization of the cells is required. In the present study, we used microarrays and analyzed the global transcription of hESC-derived cardiomyocyte clusters (CMCs) and determined similarities as well as differences compared with reference samples from fetal and adult heart tissue. In addition, we performed a focused analysis of the expression of cardiac ion channels and genes involved in the Ca(2+)-handling machinery, which in previous studies have been shown to be immature in stem cell-derived cardiomyocytes. Our results show that hESC-derived CMCs, on a global level, have a highly similar gene expression profile compared with human heart tissue, and their transcriptional phenotype was more similar to fetal than to adult heart. Despite the high similarity to heart tissue, a number of significantly differentially expressed genes were identified, providing some clues toward understanding the molecular difference between in vivo sourced tissue and stem cell derivatives generated in vitro. Interestingly, some of the cardiac-related ion channels and Ca(2+)-handling genes showed differential expression between the CMCs and heart tissues. These genes may represent candidates for future genetic engineering to create hESC-derived CMCs that better mimic the phenotype of the cardiomyocytes present in the adult human heart.

Distinct endothelial phenotypes evoked by arterial waveforms derived from atherosclerosis-susceptible and -resistant regions of human vasculature

NASA Astrophysics Data System (ADS)

Dai, Guohao; Kaazempur-Mofrad, Mohammad R.; Natarajan, Sripriya; Zhang, Yuzhi; Vaughn, Saran; Blackman, Brett R.; Kamm, Roger D.; García-Cardeña, Guillermo; Gimbrone, Michael A., Jr.

2004-10-01

Atherosclerotic lesion localization to regions of disturbed flow within certain arterial geometries, in humans and experimental animals, suggests an important role for local hemodynamic forces in atherogenesis. To explore how endothelial cells (EC) acquire functional/dysfunctional phenotypes in response to vascular region-specific flow patterns, we have used an in vitro dynamic flow system to accurately reproduce arterial shear stress waveforms on cultured human EC and have examined the effects on EC gene expression by using a high-throughput transcriptional profiling approach. The flow patterns in the carotid artery bifurcations of several normal human subjects were characterized by using 3D flow analysis based on actual vascular geometries and blood flow profiles. Two prototypic arterial waveforms, "athero-prone" and "athero-protective," were defined as representative of the wall shear stresses in two distinct regions of the carotid artery (carotid sinus and distal internal carotid artery) that are typically "susceptible" or "resistant," respectively, to atherosclerotic lesion development. These two waveforms were applied to cultured EC, and cDNA microarrays were used to analyze the differential patterns of EC gene expression. In addition, the differential effects of athero-prone vs. athero-protective waveforms were further characterized on several parameters of EC structure and function, including actin cytoskeletal organization, expression and localization of junctional proteins, activation of the NF-B transcriptional pathway, and expression of proinflammatory cytokines and adhesion molecules. These global gene expression patterns and functional data reveal a distinct phenotypic modulation in response to the wall shear stresses present in atherosclerosis-susceptible vs. atherosclerosis-resistant human arterial geometries.

O-Linked β-N-Acetylglucosaminylation (O-GlcNAcylation) in Primary and Metastatic Colorectal Cancer Clones and Effect of N-Acetyl-β-d-glucosaminidase Silencing on Cell Phenotype and Transcriptome*

PubMed Central

Yehezkel, Galit; Cohen, Liz; Kliger, Adi; Manor, Esther; Khalaila, Isam

2012-01-01

O-Linked β-N-acetylglucosamine (O-GlcNAc) glycosylation is a regulatory post-translational modification occurring on the serine or threonine residues of nucleocytoplasmic proteins. O-GlcNAcylation is dynamically regulated by O-GlcNAc transferase and O-GlcNAcase (OGA), which are responsible for O-GlcNAc addition and removal, respectively. Although O-GlcNAcylation was found to play a significant role in several pathologies such as type II diabetes and neurodegenerative diseases, the role of O-GlcNAcylation in the etiology and progression of cancer remains vague. Here, we followed O-GlcNAcylation and its catalytic machinery in metastatic clones of human colorectal cancer and the effect of OGA knockdown on cellular phenotype and on the transcriptome. The colorectal cancer SW620 metastatic clone exhibited increased O-GlcNAcylation and decreased OGA expression compared with its primary clone, SW480. O-GlcNAcylation elevation in SW620 cells, through RNA interference of OGA, resulted in phenotypic alterations that included acquisition of a fibroblast-like morphology, which coincides with epithelial metastatic progression and growth retardation. Microarray analysis revealed that OGA silencing altered the expression of about 1300 genes, mostly involved in cell movement and growth, and specifically affected metabolic pathways of lipids and carbohydrates. These findings support the involvement of O-GlcNAcylation in various aspects of tumor cell physiology and suggest that this modification may serve as a link between metabolic changes and cancer. PMID:22730328

Chipster: user-friendly analysis software for microarray and other high-throughput data.

PubMed

Kallio, M Aleksi; Tuimala, Jarno T; Hupponen, Taavi; Klemelä, Petri; Gentile, Massimiliano; Scheinin, Ilari; Koski, Mikko; Käki, Janne; Korpelainen, Eija I

2011-10-14

The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.

Chipster: user-friendly analysis software for microarray and other high-throughput data

PubMed Central

2011-01-01

Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available. PMID:21999641

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.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

ERIC Educational Resources Information Center

Tra, Yolande V.; Evans, Irene M.

2010-01-01

"BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

Diagnostic Yield of Chromosomal Microarray Analysis in a Cohort of Patients with Autism Spectrum Disorders from a Highly Consanguineous Population

ERIC Educational Resources Information Center

Al-Mamari, Watfa; Al-Saegh, Abeer; Al-Kindy, Adila; Bruwer, Zandre; Al-Murshedi, Fathiya; Al-Thihli, Khalid

2015-01-01

Autism Spectrum Disorders are a complicated group of disorders characterized with heterogeneous genetic etiologies. The genetic investigations for this group of disorders have expanded considerably over the past decade. In our study we designed a tired approach and studied the diagnostic yield of chromosomal microarray analysis on patients…

Immunological Targeting of Tumor Initiating Prostate Cancer Cells

DTIC Science & Technology

2014-10-01

clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2008-09-18

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

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

Andersen, G.L.; He, Z.; DeSantis, T.Z.

Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogeneticmore » microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer oligonucleotide probes and covers more than 10,000 gene sequences in 150 gene categories involved in carbon, nitrogen, sulfur, and phosphorus cycling, metal resistance and reduction, and organic contaminant degradation. GeoChip can be used as a generic tool for microbial community analysis, and also link microbial community structure to ecosystem functioning. Examples of the application of both arrays in different environmental samples will be described in the two subsequent sections.« less

Evaluation of a low density DNA microarray for small B-cell non-Hodgkin lymphoma differential diagnosis.

PubMed

Gillet, Jean-Pierre; Molina, Thierry Jo; Jamart, Jacques; Gaulard, Philippe; Leroy, Karen; Briere, Josette; Theate, Ivan; Thieblemont, Catherine; Bosly, Andre; Herin, Michel; Hamels, Jacques; Remacle, Jose

2009-03-01

Lymphomas are classified according to the World Health Organisation (WHO) classification which defines subtypes on the basis of clinical, morphological, immunophenotypic, molecular and cytogenetic criteria. Differential diagnosis of the subtypes is sometimes difficult, especially for small B-cell lymphoma (SBCL). Standardisation of molecular genetic assays using multiple gene expression analysis by microarrays could be a useful complement to the current diagnosis. The aim of the present study was to develop a low density DNA microarray for the analysis of 107 genes associated with B-cell non-Hodgkin lymphoma and to evaluate its performance in the diagnosis of SBCL. A predictive tool based on Fisher discriminant analysis using a training set of 40 patients including four different subtypes (follicular lymphoma n = 15, mantle cell lymphoma n = 7, B-cell chronic lymphocytic leukemia n = 6 and splenic marginal zone lymphoma n = 12) was designed. A short additional preliminary analysis to gauge the accuracy of this signature was then performed on an external set of nine patients. Using this model, eight of nine of those samples were classified successfully. This pilot study demonstrates that such a microarray tool may be a promising diagnostic approach for small B-cell non-Hodgkin lymphoma.

MAGMA: analysis of two-channel microarrays made easy.

PubMed

Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

2007-07-01

The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

Tomato Expression Database (TED): a suite of data presentation and analysis tools

PubMed Central

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at . PMID:16381976

Tomato Expression Database (TED): a suite of data presentation and analysis tools.

PubMed

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150,000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at http://ted.bti.cornell.edu.

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

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.

High-throughput DNA microarray detection of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley, Nepal.

PubMed

Inoue, Daisuke; Hinoura, Takuji; Suzuki, Noriko; Pang, Junqin; Malla, Rabin; Shrestha, Sadhana; Chapagain, Saroj Kumar; Matsuzawa, Hiroaki; Nakamura, Takashi; Tanaka, Yasuhiro; Ike, Michihiko; Nishida, Kei; Sei, Kazunari

2015-01-01

Because of heavy dependence on groundwater for drinking water and other domestic use, microbial contamination of groundwater is a serious problem in the Kathmandu Valley, Nepal. This study investigated comprehensively the occurrence of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley by applying DNA microarray analysis targeting 941 pathogenic bacterial species/groups. Water quality measurements found significant coliform (fecal) contamination in 10 of the 11 investigated groundwater samples and significant nitrogen contamination in some samples. The results of DNA microarray analysis revealed the presence of 1-37 pathogen species/groups, including 1-27 biosafety level 2 ones, in 9 of the 11 groundwater samples. While the detected pathogens included several feces- and animal-related ones, those belonging to Legionella and Arthrobacter, which were considered not to be directly associated with feces, were detected prevalently. This study could provide a rough picture of overall pathogenic bacterial contamination in the Kathmandu Valley, and demonstrated the usefulness of DNA microarray analysis as a comprehensive screening tool of a wide variety of pathogenic bacteria.

Microarray Analysis of Long Noncoding RNAs in Female Diabetic Peripheral Neuropathy Patients.

PubMed

Luo, Lin; Ji, Lin-Dan; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Zhou, Wen-Hua

2018-01-01

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus (DM). Because of its controversial pathogenesis, DPN is still not diagnosed or managed properly in most patients. In this study, human lncRNA microarrays were used to identify the differentially expressed lncRNAs in DM and DPN patients, and some of the discovered lncRNAs were further validated in additional 78 samples by quantitative realtime PCR (qRT-PCR). The microarray analysis identified 446 and 1327 differentially expressed lncRNAs in DM and DPN, respectively. The KEGG pathway analysis further revealed that the differentially expressed lncRNA-coexpressed mRNAs between DPN and DM groups were significantly enriched in the MAPK signaling pathway. The lncRNA/mRNA coexpression network indicated that BDNF and TRAF2 correlated with 6 lncRNAs. The qRT-PCR confirmed the initial microarray results. These findings demonstrated that the interplay between lncRNAs and mRNA may be involved in the pathogenesis of DPN, especially the neurotrophin-MAPK signaling pathway, thus providing relevant information for future studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

MASQOT: a method for cDNA microarray spot quality control

PubMed Central

Bylesjö, Max; Eriksson, Daniel; Sjödin, Andreas; Sjöström, Michael; Jansson, Stefan; Antti, Henrik; Trygg, Johan

2005-01-01

Background cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. Results A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. Conclusion The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process. PMID:16223442

Androgen receptor expression in breast cancer in relation to molecular phenotype: results from the Nurses' Health Study.

PubMed

Collins, Laura C; Cole, Kimberly S; Marotti, Jonathan D; Hu, Rong; Schnitt, Stuart J; Tamimi, Rulla M

2011-07-01

Previous studies have demonstrated that androgen receptor is expressed in many breast cancers, but its expression in relation to the various breast cancer subtypes as defined by molecular profiling has not been studied in detail. We constructed tissue microarrays from 3093 breast cancers that developed in women enrolled in the Nurses' Health Study. Tissue microarray sections were immunostained for estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), cytokeratin 5/6, epidermal growth factor receptor (EGFR) and androgen receptor (ER). Immunostain results were used to categorize each cancer as luminal A or B, HER2 and basal like. The relationships between androgen receptor expression and molecular subtype were analyzed. Overall, 77% of the invasive breast carcinomas were androgen receptor positive. Among 2171 invasive cancers, 64% were luminal A, 15% luminal B, 6% HER2 and 11% basal like. The frequency of androgen receptor expression varied significantly across the molecular phenotypes (P<0.0001). In particular, androgen receptor expression was commonly observed in luminal A (91%) and B (68%) cancers, but was less frequently seen in HER2 cancers (59%). Despite being defined by the absence of ER and PR expression and being considered hormonally unresponsive, 32% of basal-like cancers expressed androgen receptor. Among 246 cases of ductal carcinoma in situ, 86% were androgen receptor positive, but the frequency of androgen receptor expression differed significantly across the molecular phenotypes (P=0.001), and high nuclear grade lesions were less likely to be androgen receptor positive compared with lower-grade lesions. Androgen receptor expression is most commonly seen in luminal A and B invasive breast cancers. However, expression of androgen receptor is also seen in approximately one-third of basal-like cancers, providing further evidence that basal-like cancers represent a heterogeneous group. Our findings raise the possibility that targeting the androgen receptor pathway may represent a novel therapeutic approach to the management of patients with basal-like cancers.

Clinical application of chromosomal microarray analysis for the prenatal diagnosis of chromosomal abnormalities and copy number variations in fetuses with congenital heart disease.

PubMed

Xia, Yu; Yang, Yongchao; Huang, Shufang; Wu, Yueheng; Li, Ping; Zhuang, Jian

2018-03-24

This study aimed to determine chromosomal abnormalities and copy number variations (CNVs) in fetuses with congenital heart disease (CHD) by chromosomal microarray analysis (CMA). One hundred and ten cases with CHD detected by prenatal echocardiography were enrolled in the study; 27 cases were simple CHDs, and 83 were complex CHDs. Chromosomal microarray analysis was performed on the Affymetrix CytoScan HD platform. All annotated CNVs were validated by quantitative PCR. Chromosomal microarray analysis identified 6 cases with chromosomal abnormalities, including 2 cases with trisomy 21, 2 cases with trisomy 18, 1 case with trisomy 13, and 1 unusual case of mosaic trisomy 21. Pathogenic CNVs were detected in 15.5% (17/110) of the fetuses with CHDs, including 13 cases with CHD-associated CNVs. We further identified 10 genes as likely novel CHD candidate genes through gene functional enrichment analysis. We also found that pathogenic CMA results impacted the rate of pregnancy termination. This study shows that CMA is particularly effective for identifying chromosomal abnormalities and CNVs in fetuses with CHDs as well as having an effect on obstetrical outcomes. The elucidation of the genetic basis of CHDs will continue to expand our understanding of the etiology of CHDs. © 2018 John Wiley & Sons, Ltd.

An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis

PubMed Central

Karsten, Stanislav L.; Van Deerlin, Vivianna M. D.; Sabatti, Chiara; Gill, Lisa H.; Geschwind, Daniel H.

2002-01-01

Archival formalin-fixed, paraffin-embedded and ethanol-fixed tissues represent a potentially invaluable resource for gene expression analysis, as they are the most widely available material for studies of human disease. Little data are available evaluating whether RNA obtained from fixed (archival) tissues could produce reliable and reproducible microarray expression data. Here we compare the use of RNA isolated from human archival tissues fixed in ethanol and formalin to frozen tissue in cDNA microarray experiments. Since an additional factor that can limit the utility of archival tissue is the often small quantities available, we also evaluate the use of the tyramide signal amplification method (TSA), which allows the use of small amounts of RNA. Detailed analysis indicates that TSA provides a consistent and reproducible signal amplification method for cDNA microarray analysis, across both arrays and the genes tested. Analysis of this method also highlights the importance of performing non-linear channel normalization and dye switching. Furthermore, archived, fixed specimens can perform well, but not surprisingly, produce more variable results than frozen tissues. Consistent results are more easily obtainable using ethanol-fixed tissues, whereas formalin-fixed tissue does not typically provide a useful substrate for cDNA synthesis and labeling. PMID:11788730

MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

PubMed

Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

2017-05-01

Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.

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

Women's experiences receiving abnormal prenatal chromosomal microarray testing results.

PubMed

Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J

2013-02-01

Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.

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

PubMed

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

2013-01-01

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

Microarray 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

Ugene, a newly identified protein that is commonly over-expressed in cancer, and that binds uracil DNA-glycosylase

PubMed Central

Guo, Chunguang; Zhang, Xiaodong; Fink, Stephen P; Platzer, Petra; Wilson, Keith; Willson, James K. V.; Wang, Zhenghe; Markowitz, Sanford D

2008-01-01

Expression microarrays identified a novel transcript, designated as Ugene, whose expression is absent in normal colon and colon adenomas, but that is commonly induced in malignant colon cancers. These findings were validated by real-time PCR and Northern blot analysis in an independent panel of colon cancer cases. In addition, Ugene expression was found to be elevated in many other common cancer types, including, breast, lung, uterus, and ovary. Immunofluorescence of V5-tagged Ugene revealed it to have a nuclear localization. In a pull-down assay, uracil DNA-glycosylase 2 (UNG2), an important enzyme in the base excision repair pathway, was identified as a partner protein that binds to Ugene. Co-immunoprecipitation and Western blot analysis confirmed the binding between the endogenous Ugene and UNG2 proteins. Using deletion constructs, we find that Ugene binds to the first 25 amino acids of the UNG2 NH2-terminus. We suggest Ugene induction in cancer may contribute to the cancer phenotype by interacting with the base excision repair pathway. PMID:18676834

Contiguous deletion of the NDP, MAOA, MAOB, and EFHC2 genes in a patient with Norrie disease, severe psychomotor retardation and myoclonic epilepsy.

PubMed

Rodriguez-Revenga, L; Madrigal, I; Alkhalidi, L S; Armengol, L; González, E; Badenas, C; Estivill, X; Milà, M

2007-05-01

Norrie disease (ND) is an X-linked disorder, inherited as a recessive trait that, therefore, mostly affects males. The gene responsible for ND, called NDP, maps to the short arm of chromosome X (Xp11.4-p11.3). We report here an atypical case of ND, consisting of a patient harboring a large submicroscopic deletion affecting not only the NDP gene but also the MAOA, MAOB, and EFHC2 genes. Microarray comparative genomic hybridization (CGH) analysis showed that 11 consecutive bacterial artificial chromosome (BAC) clones, mapping around the NDP gene, were deleted. These clones span a region of about 1 Mb on Xp11.3. The deletion was ascertained by fluorescent in situ hybridization (FISH) analysis with different BAC clones located within the region. Clinical features of the proband include bilateral retinal detachment, microcephaly, severe psychomotor retardation without verbal language skills acquired, and epilepsy. The identification and molecular characterization of this case reinforces the idea of a new contiguous gene syndrome that would explain the complex phenotype shared by atypical ND patients.

Addressable droplet microarrays for single cell protein analysis.

PubMed

Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

2014-11-07

Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

Recurrent pregnancy loss evaluation combined with 24-chromosome microarray of miscarriage tissue provides a probable or definite cause of pregnancy loss in over 90% of patients.

PubMed

Popescu, F; Jaslow, C R; Kutteh, W H

2018-04-01

Will the addition of 24-chromosome microarray analysis on miscarriage tissue combined with the standard American Society for Reproductive Medicine (ASRM) evaluation for recurrent miscarriage explain most losses? Over 90% of patients with recurrent pregnancy loss (RPL) will have a probable or definitive cause identified when combining genetic testing on miscarriage tissue with the standard ASRM evaluation for recurrent miscarriage. RPL is estimated to occur in 2-4% of reproductive age couples. A probable cause can be identified in approximately 50% of patients after an ASRM recommended workup including an evaluation for parental chromosomal abnormalities, congenital and acquired uterine anomalies, endocrine imbalances and autoimmune factors including antiphospholipid syndrome. Single-center, prospective cohort study that included 100 patients seen in a private RPL clinic from 2014 to 2017. All 100 women had two or more pregnancy losses, a complete evaluation for RPL as defined by the ASRM, and miscarriage tissue evaluated by 24-chromosome microarray analysis after their second or subsequent miscarriage. Frequencies of abnormal results for evidence-based diagnostic tests considered definite or probable causes of RPL (karyotyping for parental chromosomal abnormalities, and 24-chromosome microarray evaluation for products of conception (POC); pelvic sonohysterography, hysterosalpingogram, or hysteroscopy for uterine anomalies; immunological tests for lupus anticoagulant and anticardiolipin antibodies; and blood tests for thyroid stimulating hormone (TSH), prolactin and hemoglobin A1c) were evaluated. We excluded cases where there was maternal cell contamination of the miscarriage tissue or if the ASRM evaluation was incomplete. A cost analysis for the evaluation of RPL was conducted to determine whether a proposed procedure of 24-chromome microarray evaluation followed by an ASRM RPL workup (for those RPL patients who had a normal 24-chromosome microarray evaluation) was more cost-efficient than conducting ASRM RPL workups on RPL patients followed by 24-chromosome microarray analysis (for those RPL patients who had a normal RPL workup). A definite or probable cause of pregnancy loss was identified in the vast majority (95/100; 95%) of RPL patients when a 24-chromosome pair microarray evaluation of POC testing is combined with the standard ASRM RPL workup evaluation at the time of the second or subsequent loss. The ASRM RPL workup identified an abnormality and a probable explanation for pregnancy loss in only 45/100 or 45% of all patients. A definite abnormality was identified in 67/100 patients or 67% when initial testing was performed using 24-chromosome microarray analyses on the miscarriage tissue. Only 5/100 (5%) patients, who had a euploid loss and a normal ASRM RPL workup, had a pregnancy loss without a probable or definitive cause identified. All other losses were explained by an abnormal 24-chromosome microarray analysis of the miscarriage tissue, an abnormal finding of the RPL workup, or a combination of both. Results from the cost analysis indicated that an initial approach of using a 24-chromosome microarray analysis on miscarriage tissue resulted in a 50% savings in cost to the health care system and to the patient. This is a single-center study on a small group of well-characterized women with RPL. There was an incomplete follow-up on subsequent pregnancy outcomes after evaluation, however this should not affect our principal results. The maternal age of patients varied from 26 to 45 years old. More aneuploid pregnancy losses would be expected in older women, particularly over the age of 35 years old. Evaluation of POC using 24-chromosome microarray analysis adds significantly to the ASRM recommended evaluation of RPL. Genetic evaluation on miscarriage tissue obtained at the time of the second and subsequent pregnancy losses should be offered to all couples with two or more consecutive pregnancy losses. The combination of a genetic evaluation on miscarriage tissue with an evidence-based evaluation for RPL will identify a probable or definitive cause in over 90% of miscarriages. No funding was received for this study and there are no conflicts of interest to declare. Not applicable.

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

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

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

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

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.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview.

PubMed

Skinner, Jeff; Kotliarov, Yuri; Varma, Sudhir; Mine, Karina L; Yambartsev, Anatoly; Simon, Richard; Huyen, Yentram; Morgun, Andrey

2011-07-14

DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

From Genes to Protein Mechanics on a Chip

PubMed Central

Milles, Lukas F.; Verdorfer, Tobias; Pippig, Diana A.; Nash, Michael A.; Gaub, Hermann E.

2014-01-01

Single-molecule force spectroscopy enables mechanical testing of individual proteins, however low experimental throughput limits the ability to screen constructs in parallel. We describe a microfluidic platform for on-chip protein expression and measurement of single-molecule mechanical properties. We constructed microarrays of proteins covalently attached to a chip surface, and found that a single cohesin-modified cantilever that bound to the terminal dockerin-tag of each protein remained stable over thousands of pulling cycles. The ability to synthesize and mechanically probe protein libraries presents new opportunities for high-throughput mechanical phenotyping. PMID:25194847

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.

Molecular hierarchy in neurons differentiated from mouse ES cells containing a single human chromosome 21.

PubMed

Wang, Chi Chiu; Kadota, Mitsutaka; Nishigaki, Ryuichi; Kazuki, Yasuhiro; Shirayoshi, Yasuaki; Rogers, Michael Scott; Gojobori, Takashi; Ikeo, Kazuho; Oshimura, Mitsuo

2004-02-06

Defects in neurogenesis and neuronal differentiation in the fetal brain of Down syndrome (DS) patients lead to the apparent neuropathological abnormalities and contribute to the phenotypic characters of mental retardation, and premature development of Alzheimer's disease, those being the most common phenotype in DS. In order to understand the molecular mechanism underlying the cause of phenotypic abnormalities in the DS brain, we have utilized an in vitro model of TT2F mouse embryonic stem cells containing a single human chromosome 21 (hChr21) to study neuron development and neuronal differentiation by microarray containing 15K developmentally expressed cDNAs. Defective neuronal differentiation in the presence of extra hChr21 manifested primarily the post-transcriptional and translational modification, such as Mrpl10, SNAPC3, Srprb, SF3a60 in the early neuronal stem cell stage, and Mrps18a, Eef1g, and Ubce8 in the late differentiated stage. Hierarchical clustering patterned specific expression of hChr21 gene dosage effects on neuron outgrowth, migration, and differentiation, such as Syngr2, Dncic2, Eif3sf, and Peg3.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

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

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

A Cross-Sectional Study of the Prevalence of Gastrointestinal Symptoms and Pathology in Patients With Common Variable Immunodeficiency.

PubMed

Jørgensen, Silje F; Reims, Henrik M; Frydenlund, Didrik; Holm, Kristian; Paulsen, Vemund; Michelsen, Annika E; Jørgensen, Kristin K; Osnes, Liv T; Bratlie, Jorunn; Eide, Tor J; Dahl, Christen P; Holter, Ellen; Tronstad, Rune R; Hanevik, Kurt; Brattbakk, Hans-Richard; Kaveh, Fatemeh; Fiskerstrand, Torunn; Kran, Anne-Marte B; Ueland, Thor; Karlsen, Tom H; Aukrust, Pål; Lundin, Knut E A; Fevang, Børre

2016-10-01

The objective of this study was to study the prevalence of gastrointestinal (GI) symptoms and histopathology in patients with common variable immunodeficiency (CVID) as well as linking the findings to GI infections and markers of systemic immune activation. In this cross-sectional study, we addressed GI symptoms in 103 patients and GI histopathological findings in 53 patients who underwent upper and lower endoscopic examination. The most frequent histopathological findings were linked to GI symptoms, B-cell phenotype, and markers of systemic immune activation (soluble (s)CD14, sCD25, and sCD163). Microarray analysis compared "celiac-like disease" in CVID to celiac disease. Screening for selected bacterial and viral infections in fecal samples and gut mucosal biopsies was performed. The main findings of this study were as follows: most common GI symptoms were bloating (34%), pain (30%), and diarrhea (26%). The most frequent histopathological findings were increased intraepithelial lymphocytes in the descending part of the duodenum, i.e., "celiac-like disease" (46% of patients), decreased numbers of plasma cells in GI tract mucosa (62%), and lymphoid hyperplasia (38%), none of which were associated with GI symptoms. Reduced plasma cells in GI mucosa were associated with B-cell phenotypic characteristics of CVID, and increased serum levels of sCD14 (P=0.025), sCD25 (P=0.01), and sCD163 (P=0.04). Microarray analyses distinguished between CVID patients with "celiac-like disease" and celiac disease. Positive tests for bacterial and viral infections were scarce both in fecal samples and gut mucosal biopsies, including PCR test for norovirus in biopsy specimens (0 positive tests). In conclusion, GI pathology is common in CVID, but does not necessarily cause symptoms. However, reduced plasma cells in GI mucosa were linked to systemic immune activation, "celiac-like disease" in CVID and true celiac disease appear to be different disease entities, as assessed by gene expression, and infections (including norovirus) are rarely a cause of the CVID enteropathy.

Participation of Candida albicans Transcription Factor RLM1 in Cell Wall Biogenesis and Virulence

PubMed Central

Delgado-Silva, Yolanda; Vaz, Catarina; Carvalho-Pereira, Joana; Carneiro, Catarina; Nogueira, Eugénia; Correia, Alexandra; Carreto, Laura; Silva, Sónia; Faustino, Augusto; Pais, Célia; Oliveira, Rui; Sampaio, Paula

2014-01-01

Candida albicans cell wall is important for growth and interaction with the environment. RLM1 is one of the putative transcription factors involved in the cell wall integrity pathway, which plays an important role in the maintenance of the cell wall integrity. In this work we investigated the involvement of RLM1 in the cell wall biogenesis and in virulence. Newly constructed C. albicans Δ/Δrlm1 mutants showed typical cell wall weakening phenotypes, such as hypersensitivity to Congo Red, Calcofluor White, and caspofungin (phenotype reverted in the presence of sorbitol), confirming the involvement of RLM1 in the cell wall integrity. Additionally, the cell wall of C. albicans Δ/Δrlm1 showed a significant increase in chitin (213%) and reduction in mannans (60%), in comparison with the wild-type, results that are consistent with cell wall remodelling. Microarray analysis in the absence of any stress showed that deletion of RLM1 in C. albicans significantly down-regulated genes involved in carbohydrate catabolism such as DAK2, GLK4, NHT1 and TPS1, up-regulated genes involved in the utilization of alternative carbon sources, like AGP2, SOU1, SAP6, CIT1 or GAL4, and genes involved in cell adhesion like ECE1, ALS1, ALS3, HWP1 or RBT1. In agreement with the microarray results adhesion assays showed an increased amount of adhering cells and total biomass in the mutant strain, in comparison with the wild-type. C. albicans mutant Δ/Δrlm1 strain was also found to be less virulent than the wild-type and complemented strains in the murine model of disseminated candidiasis. Overall, we showed that in the absence of RLM1 the modifications in the cell wall composition alter yeast interaction with the environment, with consequences in adhesion ability and virulence. The gene expression findings suggest that this gene participates in the cell wall biogenesis, with the mutant rearranging its metabolic pathways to allow the use of alternative carbon sources. PMID:24466000

A cross-omics toxicological evaluation of drinking water treated with different processes.

PubMed

Shi, Peng; Jia, Shuyu; Zhang, Xu-Xiang; Zhao, Fuzheng; Chen, Yajun; Zhou, Qing; Cheng, Shupei; Li, Ai-Min

2014-04-30

Cross-omics profiling and phenotypic analysis were conducted to comprehensively assess the toxicities of source of drinking water (SDW), effluent of conventional treatment (ECT) and effluent of advanced treatment (EAT) in a water treatment plant. SDW feeding increased body weight, and relative liver and kidney weights of mice. Hepatic histopathological damages and serum biochemical alterations were observed in the mice fed with SDW and ECT, but EAT feeding showed no obvious effects. Transcriptomic analysis demonstrated that exposure to water samples caused differential expression of hundreds of genes in livers. Cluster analysis of the differentially expressed genes which generated by both microarrays and digital gene expression showed similar grouping patterns. Proteomic and metabolomics analyses indicated that drinking SDW, ECT and EAT generated 59, 145 and 41 significantly altered proteins in livers and 8, 2 and 0 altered metabolites in serum, respectively. SDW was found to affect several metabolic pathways including metabolism of xenobiotics by cytochrome P450 and fatty acid metabolism. SDW and ECT might induce molecular toxicities to mice, but the advanced treatment process can reduce the potential health risk by effectively removing toxic chemicals in drinking water. Copyright © 2014 Elsevier B.V. All rights reserved.

Inheritance of a Ring Chromosome 21 in a Couple Undergoing In Vitro Fertilization (IVF): A Case Report

PubMed Central

Mazzaschi, Roberto L. P.; Love, Donald R.; Hayes, Ian; George, Alice

2011-01-01

An amniotic fluid sample from an in vitro fertilized pregnancy was referred for cytogenetic analysis based on a Down syndrome screening risk of 1 : 21. Routine cytogenetic analysis showed a nonmosaic karyotype of 46,XX,r(21)(p11.2q22.3), with partial monosomy for chromosome 21 due to a ring chromosome replacing one of the normal homologues. Detailed ultrasound scanning for the remainder of the pregnancy did not reveal any unusual findings. Parental bloods showed that the mother was mosaic for the ring 21 with a karyotype of 46,XX,r(21)(p11.2q22.3)/46,XX and the father had an unrelated Robertsonian translocation, with a karyotype of 45,XY,rob(13;14)(q10;q10). Microarray analysis of cultured amniocytes determined the extent of the deletion of chromosome 21 material in the ring. The parents were given genetic counselling, and a phenotypically normal female baby was delivered at term. This case highlights the importance of karyotyping as an initial step in the management of couples referred for in vitro fertilization. PMID:23074672

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.

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

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

Gregory Stephanopoulos

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

Low-Molecular-Weight Protein Tyrosine Phosphatase Predicts Prostate Cancer Outcome by Increasing the Metastatic Potential.

PubMed

Ruela-de-Sousa, Roberta R; Hoekstra, Elmer; Hoogland, A Marije; Queiroz, Karla C Souza; Peppelenbosch, Maikel P; Stubbs, Andrew P; Pelizzaro-Rocha, Karin; van Leenders, Geert J L H; Jenster, Guido; Aoyama, Hiroshi; Ferreira, Carmen V; Fuhler, Gwenny M

2016-04-01

Low-risk patients suffering from prostate cancer (PCa) are currently placed under active surveillance rather than undergoing radical prostatectomy. However, clear parameters for selecting the right patient for each strategy are not available, and new biomarkers and treatment modalities are needed. Low-molecular-weight protein tyrosine phosphatase (LMWPTP) could present such a target. To correlate expression levels of LMWPTP in primary PCa to clinical outcome, and determine the role of LMWPTP in prostate tumor cell biology. Acid phosphatase 1, soluble (ACP1) expression was analyzed on microarray data sets, which were subsequently used in Ingenuity Pathway Analysis. Immunohistochemistry was performed on a tissue microarray containing material of 481 PCa patients whose clinicopathologic data were recorded. PCa cell line models were used to investigate the role of LMWPTP in cell proliferation, migration, adhesion, and anoikis resistance. The association between LMWPTP expression and clinical and pathologic outcomes was calculated using chi-square correlations and multivariable Cox regression analysis. Functional consequences of LMWPTP overexpression or downregulation were determined using migration and adhesion assays, confocal microscopy, Western blotting, and proliferation assays. LMWPTP expression was significantly increased in human PCa and correlated with earlier recurrence of disease (hazard ratio [HR]:1.99; p<0.001) and reduced patient survival (HR: 1.53; p=0.04). Unbiased Ingenuity analysis comparing cancer and normal prostate suggests migratory propensities in PCa. Indeed, overexpression of LMWPTP increases PCa cell migration, anoikis resistance, and reduces activation of focal adhesion kinase/paxillin, corresponding to decreased adherence. Overexpression of LMWPTP in PCa confers a malignant phenotype with worse clinical outcome. Prospective follow-up should determine the clinical potential of LMWPTP overexpression. These findings implicate low-molecular-weight protein tyrosine phosphatase as a novel oncogene in prostate cancer and could offer the possibility of using this protein as biomarker or target for treatment of this disease. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Alteration of gene expression by alcohol exposure at early neurulation.

PubMed

Zhou, Feng C; Zhao, Qianqian; Liu, Yunlong; Goodlett, Charles R; Liang, Tiebing; McClintick, Jeanette N; Edenberg, Howard J; Li, Lang

2011-02-21

We have previously demonstrated that alcohol exposure at early neurulation induces growth retardation, neural tube abnormalities, and alteration of DNA methylation. To explore the global gene expression changes which may underline these developmental defects, microarray analyses were performed in a whole embryo mouse culture model that allows control over alcohol and embryonic variables. Alcohol caused teratogenesis in brain, heart, forelimb, and optic vesicle; a subset of the embryos also showed cranial neural tube defects. In microarray analysis (accession number GSM9545), adopting hypothesis-driven Gene Set Enrichment Analysis (GSEA) informatics and intersection analysis of two independent experiments, we found that there was a collective reduction in expression of neural specification genes (neurogenin, Sox5, Bhlhe22), neural growth factor genes [Igf1, Efemp1, Klf10 (Tieg), and Edil3], and alteration of genes involved in cell growth, apoptosis, histone variants, eye and heart development. There was also a reduction of retinol binding protein 1 (Rbp1), and de novo expression of aldehyde dehydrogenase 1B1 (Aldh1B1). Remarkably, four key hematopoiesis genes (glycophorin A, adducin 2, beta-2 microglobulin, and ceruloplasmin) were absent after alcohol treatment, and histone variant genes were reduced. The down-regulation of the neurospecification and the neurotrophic genes were further confirmed by quantitative RT-PCR. Furthermore, the gene expression profile demonstrated distinct subgroups which corresponded with two distinct alcohol-related neural tube phenotypes: an open (ALC-NTO) and a closed neural tube (ALC-NTC). Further, the epidermal growth factor signaling pathway and histone variants were specifically altered in ALC-NTO, and a greater number of neurotrophic/growth factor genes were down-regulated in the ALC-NTO than in the ALC-NTC embryos. This study revealed a set of genes vulnerable to alcohol exposure and genes that were associated with neural tube defects during early neurulation.

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.

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240