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microarray platform consistency is revealed by biologically functional analysis of gene expression profiles

BMC BIOINFORMATICS 2009年第11期10卷 1-8页

作者： Li, Zhiguang Su, Zhenqiang Wen, Zhining Shi, Leming Chen, Tao US FDA Div Genet & Reprod Toxicol Natl Ctr Toxicol Res Jefferson AR 72079 USA US FDA Div Syst Toxicol Natl Ctr Toxicol Res Jefferson AR 72079 USA

Background: Several different microarray platforms are available for measuring gene expression. There are disagreements within the microarray scientific community for intra-and inter-platform consistency of these platforms. Both high and low consistencies were demonstrated across different platforms in terms of genes with significantly differential expression. Array studies for gene expression are used to explore biological causes and effects. Therefore, consistency should eventually be evaluated in a biological setting to reveal the functional differences between the examined samples, not just a list of differentially expressed genes (DEG). In this study, we investigated whether different platforms had a high consistency from the biologically functional perspective. Results: DEG data without filtering the different probes in microarrays from different platforms generated from kidney samples of rats treated with the kidney carcinogen, aristolochic acid, in five test sites using microarrays from Affymetrix, Applied Biosystems, Agilent, and GE health platforms (two sites using Affymetrix for intra-platform comparison) were input into the Ingenuity Pathway Analysis (IPA) system for functional analysis. The functions of the DEG lists determined by IPA were compared across the four different platforms and two test sites for Affymetrix platform. Analysis results showed that there is a very high level of consistency between the two test sites using the same platform or among different platforms. The top functions determined by the different platforms were very similar and reflected carcinogenicity and toxicity of aristolochic acid in the rat kidney. Conclusion: Our results demonstrate that highly consistent biological information can be generated from different microarray platforms.

关键词： Ingenuity Pathway Analysis Differentially Express Gene microarray platform Common Function Aristolochic Acid

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Micro-perforated elastomeric poly(dimethylsiloxane) mask fabricated using high-aspect-ratio micro-pillar arrays for spatially defined surface modification: an unconventional method for establishing a microarray platform

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ANALYTICAL AND BIOANALYTICAL CHEMISTRY 2009年第4期394卷 1227-1232页

作者： Tang, Linzhi Lee, Nae Yoon Kyungwon Univ Gachon BioNano Res Inst Songnam 461701 Gyeonggi Do South Korea Kyungwon Univ Div BioNano Technol Songnam 461701 Gyeonggi Do South Korea Kyungwon Univ Coll BioNano Technol Songnam 461701 Gyeonggi Do South Korea

Herein, we introduce the fabrication of a micro-perforated elastomeric poly(dimethylsiloxane) (PDMS) mask and employ it for spatially defined surface modification. To fabricate the micro-perforated PDMS mask, high-aspect-ratio micro-pillar arrays having millimeter scale height were first fabricated via direct photopolymerization using a thiol-ene-based UV-curable adhesive. Square pillars (500 x 500 A mu m) and 200 A mu m circular pillars with 5 and 12.5 in the aspect ratios, respectively, were successfully fabricated with high pattern fidelity, reaching 2.5mm in height. Next, using the micro-pillar-array platform as a master mold, PDMS prepolymer was cast and polymerized to form an elastomeric PDMS mask having micro-perforation arrays. Alternating hydrophilic and hydrophobic surfaces were successfully obtained by oxidizing PDMS-covered Si wafer with corona discharge. Spatially defined chemical functionalities obtained by selective oxidation and subsequent silanization were clearly distinguished via colorimetric detection methods employing ninhydrin and toluidine reagents. The micro-perforated elastomeric PDMS mask enables selective modification of a surface without utilizing photoreactive chemicals and a photomask.

关键词： High-aspect-ratio micro-pillar arrays Thiol-ene adhesive Micro-perforation array Elastomeric PDMS mask Selective surface modification microarray platform

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Transcriptome sequencing and development of an expression microarray platform for the domestic ferret

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BMC GENOMICS 2010年第1期11卷 1-11页

作者： Bruder, Carl E. Yao, Suxia Larson, Francis Camp, Jeremy V. Tapp, Ronald McBrayer, Alexis Powers, Nicholas Granda, Willy Valdivia Jonsson, Colleen B. So Res Inst Birmingham AL 35205 USA Orion Integrated Biosci Inc New Rochelle NY 10805 USA Univ Louisville Ctr Predict Med Biodef & Emerging Infect Dis Louisville KY 40292 USA

Background: The ferret (Mustela putorius furo) represents an attractive animal model for the study of respiratory diseases, including influenza. Despite its importance for biomedical research, the number of reagents for molecular and immunological analysis is restricted. We present here a parallel sequencing effort to produce an extensive EST (expressed sequence tags) dataset derived from a normalized ferret cDNA library made from mRNA from ferret blood, liver, lung, spleen and brain. Results: We produced more than 500000 sequence reads that were assembled into 16000 partial ferret genes. These genes were combined with the available ferret sequences in the GenBank to develop a ferret specific microarray platform. Using this array, we detected tissue specific expression patterns which were confirmed by quantitative real time PCR assays. We also present a set of 41 ferret genes with even transcription profiles across the tested tissues, indicating their usefulness as housekeeping genes. Conclusion: The tools developed in this study allow for functional genomic analysis and make further development of reagents for the ferret model possible.

关键词： Influenza Influenza Virus Severe Acute Respiratory Syndrome microarray platform Canine Distemper Virus

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Development of a microarray platform for FFPET profiling: application to the classification of human tumors

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JOURNAL OF TRANSLATIONAL MEDICINE 2009年第1期7卷 1-16页

作者： Duenwald, Sven Zhou, Mingjie Wang, Yanqun Lejnine, Serguei Kulkarni, Amit Graves, Jaime Smith, Ryan Castle, John Tokiwa, George Fine, Bernard Dai, Hongyue Fare, Thomas Marton, Matthew Merck Res Labs Dept Mol Profiling Translat Sci Seattle WA 98109 USA Sirna Therapeut LLC Dept Lead Discovery San Francisco CA 94158 USA Custom Anal Informat Boston MA 02115 USA Epigenomics Inc Seattle WA 98101 USA Merck Res Labs Dept Mol Profiling Custom Anal Seattle WA 98109 USA Merck Res Labs Dept Mol Profiling Gene Express Lab Seattle WA 98109 USA Merck Res Labs Dept Mol Profiling Mol Informat Seattle WA 98109 USA Merck Res Labs Dept Mol Profiling Clin Mol Profiling Seattle WA 98109 USA Genentech Inc San Francisco CA 94080 USA Merck Res Labs Dept Mol Profiling Adv Technol Solut Seattle WA 98109 USA External Sci Affairs West Point PA 19486 USA

Background: mRNA profiling has become an important tool for developing and validating prognostic assays predictive of disease treatment response and outcome. Archives of annotated formalin-fixed paraffin-embedded tissues (FFPET) are available as a potential source for retrospective studies. Methods are needed to profile these FFPET samples that are linked to clinical outcomes to generate hypotheses that could lead to classifiers for clinical applications. Methods: We developed a two-color microarray-based profiling platform by optimizing target amplification, experimental design, quality control, and microarray content and applied it to the profiling of FFPET samples. We profiled a set of 50 fresh frozen (FF) breast cancer samples and assigned class labels according to the signature and method by van't Veer et al [1] and then profiled 50 matched FFPET samples to test how well the FFPET data predicted the class labels. We also compared the sorting power of classifiers derived from FFPET sample data with classifiers derived from data from matched FF samples. Results: When a classifier developed with matched FF samples was applied to FFPET data to assign samples to either "good" or "poor" outcome class labels, the classifier was able to assign the FFPET samples to the correct class label with an average error rate = 12% to 16%, respectively, with an Odds Ratio = 36.4 to 60.4, respectively. A classifier derived from FFPET data was able to predict th e class label in FFPET samples (leave-one-out cross validation) with an error rate of similar to 14% (p-value = 3.7 x 10(-7)). When applied to the matched FF samples, the FFPET-derived classifier was able to assign FF samples to the correct class labels with 96% accuracy. The single misclassification was attributed to poor sample quality, as measured by qPCR on total RNA, which emphasizes the need for sample quality control before profiling. Conclusion: We have optimized a platform for expression analyses and have shown that

关键词： Class Label microarray platform Fresh Freeze Mass Imbalance Universal Human Reference

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Practical forensic use of kinship determination using high-density SNP profiling based on a microarray platform, focusing on low-quantity DNA

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FORENSIC SCIENCE INTERNATIONAL-GENETICS 2022年 61卷 102752-102752页

作者： Yagasaki, Kayoko Mabuchi, Akihiko Higashino, Toshihide Wong, Jing Hao Nishida, Nao Fujimoto, Akihiro Tokunaga, Katsushi Univ Tokyo Grad Sch Med Dept Human Genet Bunkyo Ward 73-1 Hongo Tokyo 1130033 Japan Natl Ctr Global Hlth & Med Genome Med Sci Project Shinjuku Word 1-21-1 Toyama Tokyo 1628655 Japan Natl Ctr Global Hlth & Med Genome Med Sci Project 1-7-1 Kohnodai Ichikawa Chiba 2728516 Japan Tokyo Metropolitan Police Dept Forens Sci Lab Nerima Ward 3-35-21 Shakujiidai Tokyo 1770045 Japan

Instead of traditional short tandem repeat (STR) profiling, the genetic genealogy method, which uses hundreds of thousands of single nucleotide polymorphisms (SNPs) spread across genome-wide, has emerged as a powerful kinship determination tool and recently attracted great attention in forensic genetics. In this study, we explored the tolerance and viability of kinship discrimination based on a high-density SNP profile for forensic DNA, especially focusing on low-quantity DNA. Using the Affymetrix Genome-Wide Human SNP Array 6.0 platform (Thermo Fisher Scientific), the influence of low-quantity DNA on SNP genotype determination was evaluated. The low-quantity DNA samples failed once every few samples, the generated SNP profile had low data quality. Our investigation revealed that the SNP profile with low data quality contained many genotyping errors in which the SNP genotype changed from homozygote to heterozygote. The kinship discrimination analysis using KING software was directly influenced by these genotyping errors, which was confirmed that some unrelated pairs were mis-specified as 4th-degree relatives. We confirmed that the false heterozygous SNPs resulted in an inflation of kinship coefficient and a decrease of non-shared allele between a tested pair. To eliminate the influence of these genotyping errors and acquire an accurate kinship discrimination result, we developed a novel method to select only the robust SNPs, which stably give the genotype determination with high accuracy even in SNP profiles with low data quality. The application of our novel method led to the improved results of kinship discrimination up to the same level as in the SNP profile with high data quality. In addition, this study demonstrated the advantage of kinship analysis using a high-density SNP profile in the forensic field. It is well known that likelihood ratio calculation based on autosomal STR profile, which is the most commonly applied approach, has difficulty in gaining true

关键词： Kinship discrimination analysis SNP profile STR profile microarray platform Low-quantity DNA KING software

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Gene expression analysis of RNA purified from embryonic stem cells and embryoid body-derived cells using a high-throughput microarray platform.

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Current protocols in stem cell biology 2007年第1期Chapter 1卷 Unit1B.2页

作者： Player, Audrey Wang, Yonghong Rao, Mahendra Kawasaki, Ernest National Cancer Institute Bethesda Maryland United States

In this unit, starting with purified RNA, experimental protocols for performing microarray expression analysis of embryonic stem cell lines compared to their corresponding differentiated embryocidal bodies are described. Methods for data analysis are suggested, with the goal of determining which genes are differentially expressed between the preparations. As an example, the use of the Affymetrix microarray expression platform is described, but alternative experimental options for analysis of RNA transcript levels are also summarized. This unit suggests quality control metrics, summarizes the critical parameters necessary for obtaining reproducible experimental results, and outlines quantitative PCR methods for validating microarray results. Copyright 2007 by John Wiley & Sons, Inc.

关键词： embryonic stem cells embryoid bodies RNA expression analysis microarray platform

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Redefinition of affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements

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BMC BIOINFORMATICS 2005年第1期6卷 1-15页

作者： Carter, SL Eklund, AC Mecham, BH Kohane, IS Szallasi, Z Harvard Univ Childrens Hosp Sch Med Informat Program Boston MA 02115 USA Brigham & Womens Hosp Lab Funct Genom Cambridge MA 02139 USA

Background: Comparison of data produced on different microarray platforms often shows surprising discordance. It is not clear whether this discrepancy is caused by noisy data or by improper probe matching between platforms. We investigated whether the significant level of inconsistency between results produced by alternative gene expression microarray platforms could be reduced by stringent sequence matching of microarray probes. We mapped the short oligo probes of the Affymetrix platform onto cDNA clones of the Stanford microarray platform. Affymetrix probes were reassigned to redefined probe sets if they mapped to the same cDNA clone sequence, regardless of the original manufacturer-defined grouping. The NCI-60 gene expression profiles produced by Affymetrix HuFL platform were recalculated using these redefined probe sets and compared to previously published cDNA measurements of the same panel of RNA samples. Results: The redefined probe sets displayed a substantially higher level of cross-platform consistency at the level of gene correlation, cell line correlation and unsupervised hierarchical clustering. The same strategy allowed an almost complete correspondence of breast cancer subtype classification between Affymetrix gene chip and cDNA microarray derived gene expression data, and gave an increased level of similarity between normal lung derived gene expression profiles using the two technologies. In total, two Affymetrix gene-chip platforms were remapped to three cDNA platforms in the various cross-platform analyses, resulting in improved concordance in each case. Conclusion: We have shown that probes which target overlapping transcript sequence regions on cDNA microarrays and Affymetrix gene-chips exhibit a greater level of concordance than the corresponding Unigene or sequence matched features. This method will be useful for the integrated analysis of gene expression data generated by multiple disparate measurement platforms.

关键词： cDNA microarray microarray platform Affymetrix Probe Cross platform Affymetrix platform

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Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the microarray Quality Control (MAQC) study

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BMC GENOMICS 2008年第1期9卷 1-12页

作者： Arikawa, Emi Sun, Yanyang Wang, Jie Zhou, Qiong Ning, Baitang Dial, Stacey L. Guo, Lei Yang, Jingping SuperArray Biosci Corp Frederick MD 21704 USA US FDA Natl Ctr Toxicol Res Jefferson AR 72079 USA

Background: The microarray Quality Control (MAQC) project evaluated the inter-and intra-platform reproducibility of seven microarray platforms and three quantitative gene expression assays in profiling the expression of two commercially available Reference RNA samples (Nat Biotechnol 24:1115-22, 2006). The tested microarrays were the platforms from Affymetrix, Agilent Technologies, Applied Biosystems, GE Healthcare, Illumina, Eppendorf and the National Cancer Institute, and quantitative gene expression assays included TaqMan (R) Gene Expression PCR Assay, Standardized (Sta) RT-PCR (TM) and QuantiGene (R). The data showed great consistency in gene expression measurements across different microarray platforms, different technologies and test sites. However, SYBR (R) Green real-time PCR, another common technique utilized by half of all real-time PCR users for gene expression measurement, was not addressed in the MAQC study. In the present study, we compared the performance of SYBR Green PCR with TaqMan PCR, microarrays and other quantitative technologies using the same two Reference RNA samples as the MAQC project. We assessed SYBR Green real-time PCR using commercially available RT2 Profiler (TM) PCR Arrays from SuperArray, containing primer pairs that have been experimentally validated to ensure gene-specificity and high amplification efficiency. Results: The SYBR Green PCR Arrays exhibit good reproducibility among different users, PCR instruments and test sites. In addition, the SYBR Green PCR Arrays have the highest concordance with TaqMan PCR, and a high level of concordance with other quantitative methods and microarrays that were evaluated in this study in terms of fold-change correlation and overlap of lists of differentially expressed genes. Conclusion: These data demonstrate that SYBR Green real-time PCR delivers highly comparable results in gene expression measurement with TaqMan PCR and other high-density microarrays.

关键词： microarray platform Discordant Gene MAQC Project Quantitative platform MAQC Study

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Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

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BMC GENOMICS 2011年第1期12卷 1-19页

作者： Llorens, Franc Hummel, Manuela Pastor, Xavier Ferrer, Anna Pluvinet, Raquel Vivancos, Ana Castillo, Ester Iraola, Susana Mosquera, Ana M. Gonzalez, Eva Lozano, Juanjo Ingham, Matthew Dohm, Juliane C. Noguera, Marc Kofler, Robert Antonio del Rio, Jose Bayes, Monica Himmelbauer, Heinz Sumoy, Lauro UPF Bioinformat & Genom Program Ctr Genom Regulat CRG Barcelona Spain IBEC Mol & Cellular Neurobiotechnol Grp Barcelona Spain Univ Barcelona Dept Cell Biol Barcelona Spain Networked Biomed Res Ctr Neurodegenerat Dis CIBER Madrid Spain UPF Microarray Unit Genom Core Facil Ctr Genom Regulat CRG Barcelona Spain UPF Genom Core Facil Ctr Genom Regulat CRG Barcelona Spain Inst Predict & Personalized Med Canc IMPPC Genom Unit Badalona Spain UPF Ultrasequencing Unit Genom Core Facil Ctr Genom Regulat CRG Barcelona Spain Vall dHebron Inst Oncol Canc Genom Grp Barcelona Spain UPF Genes & Dis Program Ctr Genom Regulat CRG Barcelona Spain Hosp St Joan de Deu Endocrinol Sect Esplugas de Llobregat Spain Networked Biomed Res Ctr Diabet & Associated Meta Barcelona Spain Hosp Clin 1 & Prov Barcelona Serv Inmunol Barcelona Spain Inst Invest Biomed August Pi i Sunyer Barcelona Spain Networked Biomed Res Ctr Hepat & Digest Dis CIBER Barcelona Spain Spanish Natl Ctr Genom Anal CNAG Barcelona Spain Max Planck Inst Mol Genet Berlin Germany IRSI Caixa Badalona Spain Univ Vet Med Inst Populat Genet Vienna Austria

Background: Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. Results: By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions: We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

关键词： Epidermal Growth Factor microarray platform Digital Gene Expression Epidermal Growth Factor Stimulation Epidermal Growth Factor Treatment

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virtualArray: a R/bioconductor package to merge raw data from different microarray platforms

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BMC BIOINFORMATICS 2013年第1期14卷 1-10页

作者： Heider, Andreas Alt, Ruediger Univ Leipzig Translat Ctr Regenerat Med Leipzig D-04103 Leipzig Germany

Background: microarrays have become a routine tool to address diverse biological questions. Therefore, different types and generations of microarrays have been produced by several manufacturers over time. Likewise, the diversity of raw data deposited in public databases such as NCBI GEO or EBI ArrayExpress has grown enormously. This has resulted in databases currently containing several hundred thousand microarray samples clustered by different species, manufacturers and chip generations. While one of the original goals of these databases was to make the data available to other researchers for independent analysis and, where appropriate, integration with their own data, current software implementations could not provide that feature. Only those data sets generated on the same chip platform can be readily combined and even here there are batch effects to be taken care of. A straightforward approach to deal with multiple chip types and batch effects has been missing. The software presented here was designed to solve both of these problems in a convenient and user friendly way. Results: The virtualArray software package can combine raw data sets using almost any chip types based on current annotations from NCBI GEO or Bioconductor. After establishing congruent annotations for the raw data, virtualArray can then directly employ one of seven implemented methods to adjust for batch effects in the data resulting from differences between the chip types used. Both steps can be tuned to the preferences of the user. When the run is finished, the whole dataset is presented as a conventional Bioconductor "ExpressionSet" object, which can be used as input to other Bioconductor packages. Conclusions: Using this software package, researchers can easily integrate their own microarray data with data from public repositories or other sources that are based on different microarray chip types. Using the default approach a robust and up-to-date batch effect correction technique is applie

关键词： iPSC microarray platform Batch Effect NCBI Gene Expression Omnibus Chip Type

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