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Pang L, Cai C, Aggarwal P, Wang D, Vijay V, Bagam P, Blamer J, Matter A, Turner A, Ren L, Papineau K, Srinivasasainagendra V, Tiwari HK, Yang X, Schnackenberg L, Mattes W, Broeckel U. Predicting oncology drug-induced cardiotoxicity with donor-specific iPSC-CMs-a proof-of-concept study with doxorubicin. Toxicol Sci 2024; 200:79-94. [PMID: 38547396 PMCID: PMC11199917 DOI: 10.1093/toxsci/kfae041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/27/2024] Open
Abstract
Many oncology drugs have been found to induce cardiotoxicity in a subset of patients, which significantly limits their clinical use and impedes the benefit of lifesaving anticancer treatments. Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) carry donor-specific genetic information and have been proposed for exploring the interindividual difference in oncology drug-induced cardiotoxicity. Herein, we evaluated the inter- and intraindividual variability of iPSC-CM-related assays and presented a proof of concept to prospectively predict doxorubicin (DOX)-induced cardiotoxicity (DIC) using donor-specific iPSC-CMs. Our findings demonstrated that donor-specific iPSC-CMs exhibited greater line-to-line variability than the intraindividual variability in impedance cytotoxicity and transcriptome assays. The variable and dose-dependent cytotoxic responses of iPSC-CMs resembled those observed in clinical practice and largely replicated the reported mechanisms. By categorizing iPSC-CMs into resistant and sensitive cell lines based on their time- and concentration-related phenotypic responses to DOX, we found that the sensitivity of donor-specific iPSC-CMs to DOX may predict in vivo DIC risk. Furthermore, we identified a differentially expressed gene, DND microRNA-mediated repression inhibitor 1 (DND1), between the DOX-resistant and DOX-sensitive iPSC-CMs. Our results support the utilization of donor-specific iPSC-CMs in assessing interindividual differences in DIC. Further studies will encompass a large panel of donor-specific iPSC-CMs to identify potential novel molecular and genetic biomarkers for predicting DOX and other oncology drug-induced cardiotoxicity.
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Affiliation(s)
- Li Pang
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Chengzhong Cai
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Praful Aggarwal
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Dong Wang
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Vikrant Vijay
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Prathyusha Bagam
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Jacob Blamer
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Andrea Matter
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Amy Turner
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
| | - Lijun Ren
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Katy Papineau
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
| | - Hemant K Tiwari
- Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA
| | - Xi Yang
- Division of Pharmacology & Toxicology, Office of Cardiology, Hematology, Endocrinology, & Nephrology, Office of New Drug, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland 20903, USA
| | - Laura Schnackenberg
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - William Mattes
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas 72079, USA
| | - Ulrich Broeckel
- Department of Pediatrics, Section of Genomic Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA
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2
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Rapid Transient Transcriptional Adaptation to Hypergravity in Jurkat T Cells Revealed by Comparative Analysis of Microarray and RNA-Seq Data. Int J Mol Sci 2021; 22:ijms22168451. [PMID: 34445156 PMCID: PMC8395121 DOI: 10.3390/ijms22168451] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 07/30/2021] [Accepted: 08/02/2021] [Indexed: 12/12/2022] Open
Abstract
Cellular responses to micro- and hypergravity are rapid and complex and appear within the first few seconds of exposure. Transcriptomic analyses are a valuable tool to analyze these genome-wide cellular alterations. For a better understanding of the cellular dynamics upon altered gravity exposure, it is important to compare different time points. However, since most of the experiments are designed as endpoint measurements, the combination of cross-experiment meta-studies is inevitable. Microarray and RNA-Seq analyses are two of the main methods to study transcriptomics. In the field of altered gravity research, both methods are frequently used. However, the generation of these data sets is difficult and time-consuming and therefore the number of available data sets in this research field is limited. In this study, we investigated the comparability of microarray and RNA-Seq data and applied the results to a comparison of the transcriptomics dynamics between the hypergravity conditions during two real flight platforms and a centrifuge experiment to identify temporal adaptation processes. We performed a comparative study on an Affymetrix HTA2.0 microarray and a paired-end RNA-Seq data set originating from the same Jurkat T cell RNA samples from a short-term hypergravity experiment. The overall agreeability was high, with better sensitivity of the RNA-Seq analysis. The microarray data set showed weaknesses on the level of single upregulated genes, likely due to its normalization approach. On an aggregated level of biotypes, chromosomal distribution, and gene sets, both technologies performed equally well. The microarray showed better performance on the detection of altered gravity-related splicing events. We found that all initially altered transcripts fully adapted after 15 min to hypergravity and concluded that the altered gene expression response to hypergravity is transient and fully reversible. Based on the combined multiple-platform meta-analysis, we could demonstrate rapid transcriptional adaptation to hypergravity, the differential expression of the ATPase subunits ATP6V1A and ATP6V1D, and the cluster of differentiation (CD) molecules CD1E, CD2AP, CD46, CD47, CD53, CD69, CD96, CD164, and CD226 in hypergravity. We could experimentally demonstrate that it is possible to develop methodological evidence for the meta-analysis of individual data.
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Dakterzada F, Targa A, Benítez ID, Romero-ElKhayat L, de Gonzalo-Calvo D, Torres G, Moncusí-Moix A, Huerto R, Sánchez-de-la-Torre M, Barbé F, Piñol-Ripoll G. Identification and validation of endogenous control miRNAs in plasma samples for normalization of qPCR data for Alzheimer's disease. ALZHEIMERS RESEARCH & THERAPY 2020; 12:163. [PMID: 33278902 PMCID: PMC7719248 DOI: 10.1186/s13195-020-00735-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Accepted: 11/26/2020] [Indexed: 12/14/2022]
Abstract
Background MicroRNAs (miRNAs) are noncoding RNAs that are highly relevant as disease biomarkers. Several studies that explored the role of miRNAs in Alzheimer’s disease (AD) demonstrated their usefulness in clinical identification. Nevertheless, miRNAs that may act as endogenous controls (ECs) have not yet been established. The identification of ECs would contribute to the standardization of these biomarkers in AD. The objective of the study was to identify miRNAs that can be used as ECs in AD. Methods We evaluated 145 patients divided into two different cohorts. One was a discovery cohort of 19 women diagnosed with mild to moderate AD (Mini-Mental State Examination (MMSE) score ≥ 20) and with confirmed pathologic levels of Aβ42 in CSF. The stability assessment cohort consisted of 126 individuals: 24 subjects without AD or any kind of dementia and negative for all core CSF biomarkers of AD, 25 subjects with MCI and negative for CSF biomarkers (MCI −), 22 subjects with MCI and positive for CSF biomarkers (MCI +), and 55 subjects with AD and positive for CSF biomarkers. In the discovery cohort, a profile of 384 miRNAs was determined in the plasma by TaqMan low-density array. The best EC candidates were identified by mean-centering and concordance correlation restricted normalization methods. The stability of the EC candidates was assessed using the GeNorm, BestKeeper, and NormFinder algorithms. Results Nine miRNAs (hsa-miR-324-5p, hsa-miR-22-5p, hsa-miR-103a-2-5p, hsa-miR-362-5p, hsa-miR-425-3p, hsa-miR-423-5p, hsa-let-7i-3p, hsa-miR-532-5p, and hsa-miR-1301-3p) were identified as EC candidates in the discovery cohort. The validation results indicated that hsa-miR-103a-2-5p was the best EC, followed by hsa-miR-22-5p, hsa-miR-1301-3p, and hsa-miR-425-3p, which had similar stability values in all three algorithms. Conclusions We identified a profile of four miRNAs as potential plasma ECs to be used for normalization of miRNA expression data in studies of subjects with cognitive impairment. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-020-00735-x.
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Affiliation(s)
- F Dakterzada
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Hospital Universitari de Santa Maria, IRBLleida, Lleida, Spain
| | - A Targa
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - I D Benítez
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - L Romero-ElKhayat
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Hospital Universitari de Santa Maria, IRBLleida, Lleida, Spain
| | - D de Gonzalo-Calvo
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain
| | - G Torres
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - A Moncusí-Moix
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - R Huerto
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Hospital Universitari de Santa Maria, IRBLleida, Lleida, Spain
| | - M Sánchez-de-la-Torre
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Group of Precision Medicine in Chronic Diseases, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain
| | - F Barbé
- Translational Research in Respiratory Medicine, Hospital Universitari Arnau de Vilanova-Santa Maria, IRBLleida, Lleida, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBERES), Madrid, Spain
| | - G Piñol-Ripoll
- Unitat Trastorns Cognitius, Clinical Neuroscience Research, Hospital Universitari de Santa Maria, IRBLleida, Lleida, Spain.
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Steiner G, Marban-Doran C, Langer J, Pimenova T, Duran-Pacheco G, Sauter D, Langenkamp A, Solier C, Singer T, Bray-French K, Ducret A. Enabling Routine MHC-II-Associated Peptide Proteomics for Risk Assessment of Drug-Induced Immunogenicity. J Proteome Res 2020; 19:3792-3806. [PMID: 32786679 DOI: 10.1021/acs.jproteome.0c00309] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Major histocompatibility complex-II (MHC-II)-Associated Peptide Proteomics (MAPPs) is a mass spectrometry-based approach to identify and relatively quantitate naturally processed and presented MHC-II-associated peptides that can potentially activate T cells and contribute to the immunogenicity of a drug. Acceptance of the MAPPs technology as an appropriate preclinical (and potentially clinical) immunogenicity risk assessment tool depends not only on its technical stability and robustness but also on the ability to compare results across experiments and donors. To this end, we developed a specialized MAPPs data processing pipeline, dataMAPPs, which presents complex mass spectrometric data sets in the form of heat maps (heatMAPPs), enabling rapid and convenient comparison between conditions and donors. A customized normalization procedure based on identified endogenous peptides standardizes signal intensities within and between donors and enables cross-experimental comparison. We evaluated the technical reproducibility of the MAPPs platform using tool compounds with respect to the most prominent experimental factors and found that the systematic biological differences across donors by far outweighed any technical source of variation. We illustrate the capability of the MAPPs platform to generate data that may be used for preclinical risk assessment of drug-induced immunogenicity and discuss its applicability in the clinics.
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Affiliation(s)
- Guido Steiner
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Céline Marban-Doran
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Jessica Langer
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Tatiana Pimenova
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Gonzalo Duran-Pacheco
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Denise Sauter
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Anja Langenkamp
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Corinne Solier
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Thomas Singer
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Katharine Bray-French
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
| | - Axel Ducret
- Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Innovation Center Basel, Basel 4070, Switzerland
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5
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Liu X, Li N, Liu S, Wang J, Zhang N, Zheng X, Leung KS, Cheng L. Normalization Methods for the Analysis of Unbalanced Transcriptome Data: A Review. Front Bioeng Biotechnol 2019; 7:358. [PMID: 32039167 PMCID: PMC6988798 DOI: 10.3389/fbioe.2019.00358] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2019] [Accepted: 11/11/2019] [Indexed: 12/15/2022] Open
Abstract
Dozens of normalization methods for correcting experimental variation and bias in high-throughput expression data have been developed during the last two decades. Up to 23 methods among them consider the skewness of expression data between sample states, which are even more than the conventional methods, such as loess and quantile. From the perspective of reference selection, we classified the normalization methods for skewed expression data into three categories, data-driven reference, foreign reference, and entire gene set. We separately introduced and summarized these normalization methods designed for gene expression data with global shift between compared conditions, including both microarray and RNA-seq, based on the reference selection strategies. To our best knowledge, this is the most comprehensive review of available preprocessing algorithms for the unbalanced transcriptome data. The anatomy and summarization of these methods shed light on the understanding and appropriate application of preprocessing methods.
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Affiliation(s)
- Xueyan Liu
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medicine College of Jinan University, Shenzhen, China
| | - Nan Li
- Department of Stomatology Center, Shenzhen People's Hospital, Second Clinical Medicine College of Jinan University, Shenzhen, China
| | - Sheng Liu
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medicine College of Jinan University, Shenzhen, China
| | - Jun Wang
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medicine College of Jinan University, Shenzhen, China
| | - Ning Zhang
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medicine College of Jinan University, Shenzhen, China
| | - Xubin Zheng
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Kwong-Sak Leung
- Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Lixin Cheng
- Department of Critical Care Medicine, Shenzhen People's Hospital, The Second Clinical Medicine College of Jinan University, Shenzhen, China
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Lee YF, Lee CY, Lai LC, Tsai MH, Lu TP, Chuang EY. CellExpress: a comprehensive microarray-based cancer cell line and clinical sample gene expression analysis online system. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2018; 2018:4803287. [PMID: 29688349 PMCID: PMC7206642 DOI: 10.1093/database/bax101] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Accepted: 12/11/2017] [Indexed: 01/07/2023]
Abstract
Database URL http://cellexpress.cgm.ntu.edu.tw/.
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Affiliation(s)
- Yi-Fang Lee
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Chien-Yueh Lee
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Liang-Chuan Lai
- Graduate Institute of Physiology, National Taiwan University, Taipei, Taiwan
| | - Mong-Hsun Tsai
- Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan.,Institute of Biotechnology, National Taiwan University, Taipei, Taiwan
| | - Tzu-Pin Lu
- Department of Public Health, Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Eric Y Chuang
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.,Bioinformatics and Biostatistics Core, Center of Genomic Medicine, National Taiwan University, Taipei, Taiwan
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Zalocusky KA, Kan MJ, Hu Z, Dunn P, Thomson E, Wiser J, Bhattacharya S, Butte AJ. The 10,000 Immunomes Project: Building a Resource for Human Immunology. Cell Rep 2018; 25:513-522.e3. [PMID: 30304689 PMCID: PMC6263160 DOI: 10.1016/j.celrep.2018.09.021] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 05/01/2018] [Accepted: 09/07/2018] [Indexed: 02/06/2023] Open
Abstract
There is increasing appreciation that the immune system plays critical roles not only in the traditional domains of infection and inflammation but also in many areas of biology, including tumorigenesis, metabolism, and even neurobiology. However, one of the major barriers for understanding human immunological mechanisms is that immune assays have not been reproducibly characterized for a sufficiently large and diverse healthy human cohort. Here, we present the 10,000 Immunomes Project (10KIP), a framework for growing a diverse human immunology reference, from ImmPort, a publicly available resource of subject-level immunology data. Although some measurement types are sparse in the presently deposited ImmPort database, the extant data allow for a diversity of robust comparisons. Using 10KIP, we describe variations in serum cytokines and leukocytes by age, race, and sex; define a baseline cell-cytokine network; and describe immunologic changes in pregnancy. All data in the resource are available for visualization and download at http://10kimmunomes.org/.
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Affiliation(s)
- Kelly A Zalocusky
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Matthew J Kan
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Zicheng Hu
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Patrick Dunn
- Information Systems Health IT, Northrop Grumman, Rockville, MD 20850, USA
| | - Elizabeth Thomson
- Information Systems Health IT, Northrop Grumman, Rockville, MD 20850, USA
| | - Jeffrey Wiser
- Information Systems Health IT, Northrop Grumman, Rockville, MD 20850, USA
| | - Sanchita Bhattacharya
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Atul J Butte
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA 94158, USA; Department of Pediatrics, University of California, San Francisco, San Francisco, CA 94158, USA.
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8
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Firouzabadi FS, Vard A, Sehhati M, Mohebian M. An Optimized Framework for Cancer Prediction Using Immunosignature. JOURNAL OF MEDICAL SIGNALS & SENSORS 2018; 8:161-169. [PMID: 30181964 PMCID: PMC6116316 DOI: 10.4103/jmss.jmss_2_18] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background: Cancer is a complex disease which can engages the immune system of the patient. In this regard, determination of distinct immunosignatures for various cancers has received increasing interest recently. However, prediction accuracy and reproducibility of the computational methods are limited. In this article, we introduce a robust method for predicting eight types of cancers including astrocytoma, breast cancer, multiple myeloma, lung cancer, oligodendroglia, ovarian cancer, advanced pancreatic cancer, and Ewing sarcoma. Methods: In the proposed scheme, at first, the database is normalized with a dictionary of normalization methods that are combined with particle swarm optimization (PSO) for selecting the best normalization method for each feature. Then, statistical feature selection methods are used to separate discriminative features and they were further improved by PSO with appropriate weights as the inputs of the classification system. Finally, the support vector machines, decision tree, and multilayer perceptron neural network were used as classifiers. Results: The performance of the hybrid predictor was assessed using the holdout method. According to this method, the minimum sensitivity, specificity, precision, and accuracy of the proposed algorithm were 92.4 ± 1.1, 99.1 ± 1.1, 90.6 ± 2.1, and 98.3 ± 1.0, respectively, among the three types of classification that are used in our algorithm. Conclusion: The proposed algorithm considers all the circumstances and works with each feature in its special way. Thus, the proposed algorithm can be used as a promising framework for cancer prediction with immunosignature.
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Affiliation(s)
- Fatemeh Safaei Firouzabadi
- Student Research Committee, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Alireza Vard
- Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine and Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammadreza Sehhati
- Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine and Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammadreza Mohebian
- Department of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran
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9
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Lönnstedt IM, Nelander S. FC1000: normalized gene expression changes of systematically perturbed human cells. Stat Appl Genet Mol Biol 2017; 16:217-242. [PMID: 28862994 DOI: 10.1515/sagmb-2016-0072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The systematic study of transcriptional responses to genetic and chemical perturbations in human cells is still in its early stages. The largest available dataset to date is the newly released L1000 compendium. With its 1.3 million gene expression profiles of treated human cells it offers many opportunities for biomedical data mining, but also data normalization challenges of new dimensions. We developed a novel and practical approach to obtain accurate estimates of fold change response profiles from L1000, based on the RUV (Remove Unwanted Variation) statistical framework. Extending RUV to a big data setting, we propose an estimation procedure, in which an underlying RUV model is tuned by feedback through dataset specific statistical measures, reflecting p-value distributions and internal gene knockdown controls. Applying these metrics - termed evaluation endpoints - to disjoint data splits and integrating the results to select an optimal normalization, the procedure reduces bias and noise in the L1000 data, which in turn broadens the potential of this resource for pharmacological and functional genomic analyses. Our pipeline and normalization results are distributed as an R package (nelanderlab.org/FC1000.html).
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10
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Sbarrato T, Spriggs RV, Wilson L, Jones C, Dudek K, Bastide A, Pichon X, Pöyry T, Willis AE. An improved analysis methodology for translational profiling by microarray. RNA (NEW YORK, N.Y.) 2017; 23:1601-1613. [PMID: 28842509 PMCID: PMC5648029 DOI: 10.1261/rna.060525.116] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Accepted: 07/27/2017] [Indexed: 06/07/2023]
Abstract
Translational regulation plays a central role in the global gene expression of a cell, and detection of such regulation has allowed deciphering of critical biological mechanisms. Genome-wide studies of the regulation of translation (translatome) performed on microarrays represent a substantial proportion of studies, alongside with recent advances in deep-sequencing methods. However, there has been a lack of development in specific processing methodologies that deal with the distinct nature of translatome array data. In this study, we confirm that polysome profiling yields skewed data and thus violates the conventional transcriptome analysis assumptions. Using a comprehensive simulation of translatome array data varying the percentage and symmetry of deregulation, we show that conventional analysis methods (Quantile and LOESS normalizations) and statistical tests failed, respectively, to correctly normalize the data and to identify correctly deregulated genes (DEGs). We thus propose a novel analysis methodology available as a CRAN package; Internal Control Analysis of Translatome (INCATome) based on a normalization tied to a group of invariant controls. We confirm that INCATome outperforms the other normalization methods and allows a stringent identification of DEGs. More importantly, INCATome implementation on a biological translatome data set (cells silenced for splicing factor PSF) resulted in the best normalization performance and an improved validation concordance for identification of true positive DEGs. Finally, we provide evidence that INCATome is able to infer novel biological pathways with superior discovery potential, thus confirming the benefits for researchers of implementing INCATome for future translatome studies as well as for existing data sets to generate novel avenues for research.
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Affiliation(s)
- Thomas Sbarrato
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
- Aix Marseille Université, LAI UM 61, Marseille F-13288, France
- Inserm, UMR_S 1067, Marseille F-13288, France
- CNRS, UMR 7333, Marseille F-13288, France
| | - Ruth V Spriggs
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Lindsay Wilson
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Carolyn Jones
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Kate Dudek
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Amandine Bastide
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Xavier Pichon
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Tuija Pöyry
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
| | - Anne E Willis
- Medical Research Council Toxicology Unit, Leicester LE1 9HN, United Kingdom
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11
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Adriaens ME, Prickaerts P, Chan-Seng-Yue M, van den Beucken T, Dahlmans VEH, Eijssen LM, Beck T, Wouters BG, Voncken JW, Evelo CTA. Quantitative analysis of ChIP-seq data uncovers dynamic and sustained H3K4me3 and H3K27me3 modulation in cancer cells under hypoxia. Epigenetics Chromatin 2016; 9:48. [PMID: 27822313 PMCID: PMC5090954 DOI: 10.1186/s13072-016-0090-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 09/02/2016] [Indexed: 01/16/2023] Open
Abstract
Background A comprehensive assessment of the epigenetic dynamics in cancer cells is the key to understanding the molecular mechanisms underlying cancer and to improving cancer diagnostics, prognostics and treatment. By combining genome-wide ChIP-seq epigenomics and microarray transcriptomics, we studied the effects of oxygen deprivation and subsequent reoxygenation on histone 3 trimethylation of lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in a breast cancer cell line, serving as a model for abnormal oxygenation in solid tumors. A priori, epigenetic markings and gene expression levels not only are expected to vary greatly between hypoxic and normoxic conditions, but also display a large degree of heterogeneity across the cell population. Where traditionally ChIP-seq data are often treated as dichotomous data, the model and experiment here necessitate a quantitative, data-driven analysis of both datasets. Results We first identified genomic regions with sustained epigenetic markings, which provided a sample-specific reference enabling quantitative ChIP-seq data analysis. Sustained H3K27me3 marking was located around centromeres and intergenic regions, while sustained H3K4me3 marking is associated with genes involved in RNA binding, translation and protein transport and localization. Dynamic marking with both H3K4me3 and H3K27me3 (hypoxia-induced bivalency) was found in CpG-rich regions at loci encoding factors that control developmental processes, congruent with observations in embryonic stem cells. Conclusions In silico-identified epigenetically sustained and dynamic genomic regions were confirmed through ChIP-PCR in vitro, and obtained results are corroborated by published data and current insights regarding epigenetic regulation. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0090-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Michiel E Adriaens
- Maastricht Centre for Systems Biology - MaCSBio, Maastricht University, Maastricht, The Netherlands.,Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
| | - Peggy Prickaerts
- Department of Molecular Genetics, Maastricht University, Maastricht, The Netherlands
| | - Michelle Chan-Seng-Yue
- Departments of Informatics and Bio-computing, University Health Network, Toronto, ON Canada.,Heart Centre Biobank, The Hospital for Sick Children, Toronto, ON Canada
| | - Twan van den Beucken
- Princess Margaret Cancer Centre and Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON Canada.,Maastricht Radiation Oncology (MaastRO) Laboratory, Maastricht University, Maastricht, The Netherlands
| | - Vivian E H Dahlmans
- Department of Molecular Genetics, Maastricht University, Maastricht, The Netherlands
| | - Lars M Eijssen
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
| | - Timothy Beck
- Departments of Informatics and Bio-computing, University Health Network, Toronto, ON Canada.,Human Longevity Inc., San Diego, CA USA
| | - Bradly G Wouters
- Princess Margaret Cancer Centre and Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON Canada.,Maastricht Radiation Oncology (MaastRO) Laboratory, Maastricht University, Maastricht, The Netherlands
| | - Jan Willem Voncken
- Department of Molecular Genetics, Maastricht University, Maastricht, The Netherlands
| | - Chris T A Evelo
- Department of Bioinformatics - BiGCaT, Maastricht University, Maastricht, The Netherlands
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12
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Prickaerts P, Adriaens ME, Beucken TVD, Koch E, Dubois L, Dahlmans VEH, Gits C, Evelo CTA, Chan-Seng-Yue M, Wouters BG, Voncken JW. Hypoxia increases genome-wide bivalent epigenetic marking by specific gain of H3K27me3. Epigenetics Chromatin 2016; 9:46. [PMID: 27800026 PMCID: PMC5080723 DOI: 10.1186/s13072-016-0086-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 08/30/2016] [Indexed: 12/15/2022] Open
Abstract
Background Trimethylation at histone H3 lysine 4 (H3K4me3) and lysine 27 (H3K27me3) controls gene activity during development and differentiation. Whether H3K4me3 and H3K27me3 changes dynamically in response to altered microenvironmental conditions, including low-oxygen conditions commonly present in solid tumors, is relatively unknown. Demethylation of H3K4me3 and H3K27me3 is mediated by oxygen and 2-oxoglutarate dioxygenases enzymes, suggesting that oxygen deprivation (hypoxia) may influence histone trimethylation. Using the MCF7 breast epithelial adenocarcinoma cell model, we have determined the relationship between epigenomic and transcriptomic reprogramming as a function of fluctuating oxygen tension. Results We find that in MCF7, H3K4me3 and H3K27me3 marks rapidly increase at specific locations throughout the genome and are largely reversed upon reoxygenation. Whereas dynamic changes are relatively highest for H3K27me3 marking under hypoxic conditions, H3K4me3 occupation is identified as the defining epigenetic marker of transcriptional control. In agreement with the global increase of H3K27 trimethylation, we provide direct evidence that the histone H3K27me3 demethylase KDM6B/JMJD3 is inactivated by limited oxygen. In situ immunohistochemical analysis confirms a marked rise of histone trimethylation in hypoxic tumor areas. Acquisition of H3K27me3 at H3K4me3-marked loci results in a striking increase in “bivalent” epigenetic marking. Hypoxia-induced bivalency substantially overlaps with embryonal stem cell-associated genic bivalency and is retained at numerous loci upon reoxygenation. Transcriptional activity is selectively and progressively dampened at bivalently marked loci upon repeated exposure to hypoxia, indicating that this subset of genes uniquely maintains the potential for epigenetic regulation by KDM activity. Conclusions These data suggest that dynamic regulation of the epigenetic state within the tumor environment may have important consequences for tumor plasticity and biology. Electronic supplementary material The online version of this article (doi:10.1186/s13072-016-0086-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Peggy Prickaerts
- Department of Molecular Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Michiel E Adriaens
- Department of Bioinformatics (BiGCaT), Maastricht University Medical Centre, Maastricht, The Netherlands.,Maastricht Centre for Systems Biology (MaCSBio), Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Twan van den Beucken
- Maastricht Radiation Oncology (MaastRO) Laboratory, Maastricht University Medical Centre, Maastricht, The Netherlands.,Princess Margaret Cancer Centre and Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON Canada
| | - Elizabeth Koch
- Princess Margaret Cancer Centre and Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON Canada
| | - Ludwig Dubois
- Maastricht Radiation Oncology (MaastRO) Laboratory, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Vivian E H Dahlmans
- Department of Molecular Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Caroline Gits
- Department of Molecular Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Chris T A Evelo
- Department of Bioinformatics (BiGCaT), Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Michelle Chan-Seng-Yue
- Informatics and Bio-computing Program, Ontario Institute for Cancer Research, Toronto, ON Canada
| | - Bradly G Wouters
- Maastricht Radiation Oncology (MaastRO) Laboratory, Maastricht University Medical Centre, Maastricht, The Netherlands.,Princess Margaret Cancer Centre and Campbell Family Institute for Cancer Research, University Health Network, Toronto, ON Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON Canada.,Department of Radiation Oncology, University of Toronto, Toronto, ON Canada
| | - Jan Willem Voncken
- Department of Molecular Genetics, Maastricht University Medical Centre, Maastricht, The Netherlands
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13
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Boizard F, Brunchault V, Moulos P, Breuil B, Klein J, Lounis N, Caubet C, Tellier S, Bascands JL, Decramer S, Schanstra JP, Buffin-Meyer B. A capillary electrophoresis coupled to mass spectrometry pipeline for long term comparable assessment of the urinary metabolome. Sci Rep 2016; 6:34453. [PMID: 27694997 PMCID: PMC5046087 DOI: 10.1038/srep34453] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 09/14/2016] [Indexed: 01/31/2023] Open
Abstract
Although capillary electrophoresis coupled to mass spectrometry (CE-MS) has potential application in the field of metabolite profiling, very few studies actually used CE-MS to identify clinically useful body fluid metabolites. Here we present an optimized CE-MS setup and analysis pipeline to reproducibly explore the metabolite content of urine. We show that the use of a beveled tip capillary improves the sensitivity of detection over a flat tip. We also present a novel normalization procedure based on the use of endogenous stable urinary metabolites identified in the combined metabolome of 75 different urine samples from healthy and diseased individuals. This method allows a highly reproducible comparison of the same sample analyzed nearly 130 times over a range of 4 years. To demonstrate the use of this pipeline in clinical research we compared the urinary metabolome of 34 newborns with ureteropelvic junction (UPJ) obstruction and 15 healthy newborns. We identified 32 features with differential urinary abundance. Combination of the 32 compounds in a SVM classifier predicted with 76% sensitivity and 86% specificity UPJ obstruction in a separate validation cohort of 24 individuals. Thus, this study demonstrates the feasibility to use CE-MS as a tool for the identification of clinically relevant urinary metabolites.
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Affiliation(s)
- Franck Boizard
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Valérie Brunchault
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | | | - Benjamin Breuil
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Julie Klein
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Nadia Lounis
- Unité de Recherche Clinique Pédiatrique, Module Plurithématique Pédiatrique, Centre d'Investigation Clinique - Hôpital des Enfants, Toulouse, France
| | - Cécile Caubet
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Stéphanie Tellier
- CHU Toulouse, Hôpital des Enfants, Service de Néphrologie - Médecine Interne - Hypertension Pédiatrique, Toulouse, France
| | - Jean-Loup Bascands
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Stéphane Decramer
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France.,CHU Toulouse, Hôpital des Enfants, Service de Néphrologie - Médecine Interne - Hypertension Pédiatrique, Toulouse, France
| | - Joost P Schanstra
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
| | - Bénédicte Buffin-Meyer
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1048, Institut of Cardiovascular and Metabolic Disease, Equipe 12, 1 avenue Jean Poulhès, BP 84225, 31432 Toulouse Cedex 4, France.,Université Toulouse III Paul-Sabatier Toulouse, France
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14
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Filtrating colorectal cancer associated genes by integrated analyses of global DNA methylation and hydroxymethylation in cancer and normal tissue. Sci Rep 2016; 6:31826. [PMID: 27546520 PMCID: PMC4992821 DOI: 10.1038/srep31826] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Accepted: 07/27/2016] [Indexed: 02/07/2023] Open
Abstract
Recently, 5-hydroxymethylcytosine patterning across the tumor genome was considered as a hallmark of cancer development and progression. However, locus-specific difference of hydroxymethylation between colorectal cancer and normal tissue is unknown. In this study, we performed a newly developed method, HMST-seq, to profile 726 aberrant methylated loci and 689 aberrant hydroxymethylated loci synchronously in genome wide of colorectal cancers, majority of which presented higher methylation or lower hydroxymethylationin than in normal group. Besides, abnormal hydroxymethylated modification was more frequently occur at proximal regions close to TSSs and TSSs regions than abnormal methylation. Subsequently, we screened four genes (ALOX15, GHRHR, TFPI2 and TKTL1) with aberrant methylation and aberrant hydroxymethylation at some genome position by functional enrichment analysis as candidate genes associated with colorectal cancer. Our results may allow us to select differentially epigenetically modified target genes implicated in colorectal cancer tumorigenesis.
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15
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Sun X, Chung TH, Tan D, Kim A. Practical guidelines and consideration of using RRHP for 5hmC detection. Epigenomics 2016; 8:225-35. [PMID: 26791605 DOI: 10.2217/epi.15.105] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
5-hydroxymethylcytosine (5hmC) is an epigenetic modification, which has been associated with gene expression in many biological contexts. Reduced representation hydroxymethylation profiling was developed as an enzymatic-based method for genome-wide 5hmC detection. It exploits β-glucosyltransferase to inhibit enzymatic cleavage of adapters ligated to a genomic library, allowing only fragments with glucosylated 5hmC residues at adapter junctions to be amplified and sequenced. The simple workflow and high sensitivity make it an efficient assay for 5hmC mapping. In this review, we discuss some technical consideration in applying reduced representation hydroxymethylation profiling, such as the use of alternative restriction enzymes for increased genomic coverage in different species, application of control libraries and specifications for multiplexing, data processing and normalization.
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Affiliation(s)
- Xueguang Sun
- Zymo Research Corporation, 17062 Murphy Avenue, Irvine, CA 92614, USA
| | - Tzu Hung Chung
- Zymo Research Corporation, 17062 Murphy Avenue, Irvine, CA 92614, USA
| | - Darany Tan
- Zymo Research Corporation, 17062 Murphy Avenue, Irvine, CA 92614, USA
| | - Angela Kim
- Zymo Research Corporation, 17062 Murphy Avenue, Irvine, CA 92614, USA
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16
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Heckel T, Schmucki R, Berrera M, Ringshandl S, Badi L, Steiner G, Ravon M, Küng E, Kuhn B, Kratochwil NA, Schmitt G, Kiialainen A, Nowaczyk C, Daff H, Khan AP, Lekolool I, Pelle R, Okoth E, Bishop R, Daubenberger C, Ebeling M, Certa U. Functional analysis and transcriptional output of the Göttingen minipig genome. BMC Genomics 2015; 16:932. [PMID: 26573612 PMCID: PMC4647470 DOI: 10.1186/s12864-015-2119-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 10/20/2015] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND In the past decade the Göttingen minipig has gained increasing recognition as animal model in pharmaceutical and safety research because it recapitulates many aspects of human physiology and metabolism. Genome-based comparison of drug targets together with quantitative tissue expression analysis allows rational prediction of pharmacology and cross-reactivity of human drugs in animal models thereby improving drug attrition which is an important challenge in the process of drug development. RESULTS Here we present a new chromosome level based version of the Göttingen minipig genome together with a comparative transcriptional analysis of tissues with pharmaceutical relevance as basis for translational research. We relied on mapping and assembly of WGS (whole-genome-shotgun sequencing) derived reads to the reference genome of the Duroc pig and predict 19,228 human orthologous protein-coding genes. Genome-based prediction of the sequence of human drug targets enables the prediction of drug cross-reactivity based on conservation of binding sites. We further support the finding that the genome of Sus scrofa contains about ten-times less pseudogenized genes compared to other vertebrates. Among the functional human orthologs of these minipig pseudogenes we found HEPN1, a putative tumor suppressor gene. The genomes of Sus scrofa, the Tibetan boar, the African Bushpig, and the Warthog show sequence conservation of all inactivating HEPN1 mutations suggesting disruption before the evolutionary split of these pig species. We identify 133 Sus scrofa specific, conserved long non-coding RNAs (lncRNAs) in the minipig genome and show that these transcripts are highly conserved in the African pigs and the Tibetan boar suggesting functional significance. Using a new minipig specific microarray we show high conservation of gene expression signatures in 13 tissues with biomedical relevance between humans and adult minipigs. We underline this relationship for minipig and human liver where we could demonstrate similar expression levels for most phase I drug-metabolizing enzymes. Higher expression levels and metabolic activities were found for FMO1, AKR/CRs and for phase II drug metabolizing enzymes in minipig as compared to human. The variability of gene expression in equivalent human and minipig tissues is considerably higher in minipig organs, which is important for study design in case a human target belongs to this variable category in the minipig. The first analysis of gene expression in multiple tissues during development from young to adult shows that the majority of transcriptional programs are concluded four weeks after birth. This finding is in line with the advanced state of human postnatal organ development at comparative age categories and further supports the minipig as model for pediatric drug safety studies. CONCLUSIONS Genome based assessment of sequence conservation combined with gene expression data in several tissues improves the translational value of the minipig for human drug development. The genome and gene expression data presented here are important resources for researchers using the minipig as model for biomedical research or commercial breeding. Potential impact of our data for comparative genomics, translational research, and experimental medicine are discussed.
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Affiliation(s)
- Tobias Heckel
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Roland Schmucki
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Marco Berrera
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Stephan Ringshandl
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Laura Badi
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Guido Steiner
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Morgane Ravon
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Erich Küng
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Bernd Kuhn
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Nicole A Kratochwil
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Georg Schmitt
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Anna Kiialainen
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Corinne Nowaczyk
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Hamina Daff
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Azinwi Phina Khan
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Isaac Lekolool
- International Livestock Research Institute (ILRI), PO Box 30709, Nairobi, 00100, Kenya.
| | - Roger Pelle
- International Livestock Research Institute (ILRI), PO Box 30709, Nairobi, 00100, Kenya.
| | - Edward Okoth
- International Livestock Research Institute (ILRI), PO Box 30709, Nairobi, 00100, Kenya.
| | - Richard Bishop
- International Livestock Research Institute (ILRI), PO Box 30709, Nairobi, 00100, Kenya.
| | - Claudia Daubenberger
- Swiss Tropical and Public Health Institute (Swiss TPH), Socinstr. 57, CH 4002, Basel, Switzerland.
| | - Martin Ebeling
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
| | - Ulrich Certa
- Roche Pharmaceutical Research and Early Development (pRED), Roche Innovation Center Basel, Grenzacherstrasse 124, 4070, Basel, Switzerland.
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17
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Wachter A, Bernhardt S, Beissbarth T, Korf U. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery. ACTA ACUST UNITED AC 2015; 4:520-39. [PMID: 27600238 PMCID: PMC4996411 DOI: 10.3390/microarrays4040520] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2015] [Revised: 10/12/2015] [Accepted: 10/20/2015] [Indexed: 12/21/2022]
Abstract
Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA) were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.
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Affiliation(s)
- Astrid Wachter
- Statistical Bioinformatics, Department of Medical Statistics, University Medical Center Goettingen, Humboldtallee 32, D-37073 Goettingen, Germany.
| | | | - Tim Beissbarth
- Statistical Bioinformatics, Department of Medical Statistics, University Medical Center Goettingen, Humboldtallee 32, D-37073 Goettingen, Germany.
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18
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Mimoto MS, Kwon S, Green YS, Goldman D, Christian JL. GATA2 regulates Wnt signaling to promote primitive red blood cell fate. Dev Biol 2015; 407:1-11. [PMID: 26365900 DOI: 10.1016/j.ydbio.2015.08.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2015] [Revised: 08/06/2015] [Accepted: 08/13/2015] [Indexed: 10/23/2022]
Abstract
Primitive erythropoiesis is regulated in a non cell-autonomous fashion across evolution from frogs to mammals. In Xenopus laevis, signals from the overlying ectoderm are required to induce the mesoderm to adopt an erythroid fate. Previous studies in our lab identified the transcription factor GATA2 as a key regulator of this ectodermal signal. To identify GATA2 target genes in the ectoderm required for red blood cell formation in the mesoderm, we used microarray analysis to compare gene expression in ectoderm from GATA2 depleted and wild type embryos. Our analysis identified components of the non-canonical and canonical Wnt pathways as being reciprocally up- and down-regulated downstream of GATA2 in both mesoderm and ectoderm. We show that up-regulation of canonical Wnt signaling during gastrulation blocks commitment to a hematopoietic fate while down-regulation of non-canonical Wnt signaling impairs erythroid differentiation. Our results are consistent with a model in which GATA2 contributes to inhibition of canonical Wnt signaling, thereby permitting progenitors to exit the cell cycle and commit to a hematopoietic fate. Subsequently, activation of non-canonical Wnt signaling plays a later role in enabling these progenitors to differentiate as mature red blood cells.
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Affiliation(s)
- Mizuho S Mimoto
- Department of Cell and Developmental Biology Oregon Health and Science University, School of Medicine, Portland, OR 97239-3098, USA
| | - Sunjong Kwon
- Department of Cell and Developmental Biology Oregon Health and Science University, School of Medicine, Portland, OR 97239-3098, USA
| | - Yangsook Song Green
- Department of Neurobiology and Anatomy and Internal Medicine, Division of Hematology and Hematologic Malignancies University of Utah, School of Medicine, Salt Lake City, UT 94132, USA
| | - Devorah Goldman
- Department of Cell and Developmental Biology Oregon Health and Science University, School of Medicine, Portland, OR 97239-3098, USA
| | - Jan L Christian
- Department of Neurobiology and Anatomy and Internal Medicine, Division of Hematology and Hematologic Malignancies University of Utah, School of Medicine, Salt Lake City, UT 94132, USA.
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19
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Hochrein J, Zacharias HU, Taruttis F, Samol C, Engelmann JC, Spang R, Oefner PJ, Gronwald W. Data Normalization of (1)H NMR Metabolite Fingerprinting Data Sets in the Presence of Unbalanced Metabolite Regulation. J Proteome Res 2015; 14:3217-28. [PMID: 26147738 DOI: 10.1021/acs.jproteome.5b00192] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Data normalization is an essential step in NMR-based metabolomics. Conducted properly, it improves data quality and removes unwanted biases. The choice of the appropriate normalization method is critical and depends on the inherent properties of the data set in question. In particular, the presence of unbalanced metabolic regulation, where the different specimens and cohorts under investigation do not contain approximately equal shares of up- and down-regulated features, may strongly influence data normalization. Here, we demonstrate the suitability of the Shapiro-Wilk test to detect such unbalanced regulation. Next, employing a Latin-square design consisting of eight metabolites spiked into a urine specimen at eight different known concentrations, we show that commonly used normalization and scaling methods fail to retrieve true metabolite concentrations in the presence of increasing amounts of glucose added to simulate unbalanced regulation. However, by learning the normalization parameters on a subset of nonregulated features only, Linear Baseline Normalization, Probabilistic Quotient Normalization, and Variance Stabilization Normalization were found to account well for different dilutions of the samples without distorting the true spike-in levels even in the presence of marked unbalanced metabolic regulation. Finally, the methods described were applied successfully to a real world example of unbalanced regulation, namely, a set of plasma specimens collected from patients with and without acute kidney injury after cardiac surgery with cardiopulmonary bypass use.
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Affiliation(s)
- Jochen Hochrein
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Helena U Zacharias
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Franziska Taruttis
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Claudia Samol
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Julia C Engelmann
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Rainer Spang
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Peter J Oefner
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
| | - Wolfram Gronwald
- Institute of Functional Genomics, University of Regensburg, Josef-Engert-Str. 9, 93053 Regensburg, Germany
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Wen J, Leucci E, Vendramin R, Kauppinen S, Lund AH, Krogh A, Parker BJ. Transcriptome dynamics of the microRNA inhibition response. Nucleic Acids Res 2015; 43:6207-21. [PMID: 26089393 PMCID: PMC4513874 DOI: 10.1093/nar/gkv603] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
We report a high-resolution time series study of transcriptome dynamics following antimiR-mediated inhibition of miR-9 in a Hodgkin lymphoma cell-line—the first such dynamic study of the microRNA inhibition response—revealing both general and specific aspects of the physiological response. We show miR-9 inhibition inducing a multiphasic transcriptome response, with a direct target perturbation before 4 h, earlier than previously reported, amplified by a downstream peak at ∼32 h consistent with an indirect response due to secondary coherent regulation. Predictive modelling indicates a major role for miR-9 in post-transcriptional control of RNA processing and RNA binding protein regulation. Cluster analysis identifies multiple co-regulated gene regulatory modules. Functionally, we observe a shift over time from mRNA processing at early time points to translation at later time points. We validate the key observations with independent time series qPCR and we experimentally validate key predicted miR-9 targets. Methodologically, we developed sensitive functional data analytic predictive methods to analyse the weak response inherent in microRNA inhibition experiments. The methods of this study will be applicable to similar high-resolution time series transcriptome analyses and provides the context for more accurate experimental design and interpretation of future microRNA inhibition studies.
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Affiliation(s)
- Jiayu Wen
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark
| | - Eleonora Leucci
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Laboratory for Molecular Cancer Biology, Center for the Biology of Disease, VIB, 3000 Leuven, Belgium; Laboratory for Molecular Cancer Biology, Center of Human Genetics, VIB, 3000 Leuven, Belgium
| | - Roberto Vendramin
- Laboratory for Molecular Cancer Biology, Center for the Biology of Disease, VIB, 3000 Leuven, Belgium; Laboratory for Molecular Cancer Biology, Center of Human Genetics, VIB, 3000 Leuven, Belgium
| | - Sakari Kauppinen
- Department of Haematology, Aalborg University Hospital, A.C. Meyers Vnge 15, 2450 Copenhagen SV, Denmark
| | - Anders H Lund
- Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark
| | - Anders Krogh
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark
| | - Brian J Parker
- The Bioinformatics Centre, Department of Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 30 Biopolis street, #07-01, Singapore 138671
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Yang XH, Wang B, Cunningham JM. Identification of epigenetic modifications that contribute to pathogenesis in therapy-related AML: Effective integration of genome-wide histone modification with transcriptional profiles. BMC Med Genomics 2015; 8 Suppl 2:S6. [PMID: 26043758 PMCID: PMC4460748 DOI: 10.1186/1755-8794-8-s2-s6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Background Therapy-related, secondary acute myeloid leukemia (t-AML) is an increasingly frequent complication of intensive chemotherapy. This malignancy is often characterized by abnormalities of chromosome 7, including large deletions or chromosomal loss. A variety of studies suggest that decreased expression of the EZH2 gene located at 7q36.1 is critical in disease pathogenesis. This histone methyltransferase has been implicated in transcriptional repression through modifying histone H3 on lysine 27 (H3k27). However, the critical target genes of EZH2 and their regulatory roles remain unclear. Method To characterize the subset of EZH2 target genes that might contribute to t-AML pathogenesis, we developed a novel computational analysis to integrate tissue-specific histone modifications and genome-wide transcriptional regulation. Initial integrative analysis utilized a novel "seq2gene" strategy to explore largely the target genes of chromatin immuneprecipitation sequencing (ChIP-seq) enriched regions. By combining seq2gene with our Phenotype-Genotype-Network (PGNet) algorithm, we enriched genes with similar expression profiles and genomic or functional characteristics into "biomodules". Results Initial studies identified SEMA3A (semaphoring 3A) as a novel oncogenic candidate that is regulated by EZH2-silencing, using data derived from both normal and leukemic cell lines as well as murine cells deficient in EZH2. A microsatellite marker at the SEMA3A promoter has been associated with chemosensitivity and radiosensitivity. Notably, our subsequent studies in primary t-AML demonstrate an expected up-regulation of SEMA3A that is EZH2-modulated. Furthermore, we have identified three biomodules that are co-expressed with SEMA3A and up-regulated in t-AML, one of which consists of previously characterized EZH2-repressed gene targets. The other two biomodules include MAPK8 and TATA box targets. Together, our studies suggest an important role for EZH2 targets in t-AML pathogenesis that warrants further study. Conclusion These developed computational algorithms and systems biology strategies will enhance the knowledge discovery and hypothesis-driven analysis of multiple next generation sequencing data, for t-AML and other complex diseases.
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Vu LT, Keschrumrus V, Zhang X, Zhong JF, Su Q, Kabeer MH, Loudon WG, Li SC. Tissue elasticity regulated tumor gene expression: implication for diagnostic biomarkers of primitive neuroectodermal tumor. PLoS One 2015; 10:e0120336. [PMID: 25774514 PMCID: PMC4361745 DOI: 10.1371/journal.pone.0120336] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2013] [Accepted: 02/05/2015] [Indexed: 12/19/2022] Open
Abstract
Background The tumor microenvironment consists of both physical and chemical factors. Tissue elasticity is one physical factor contributing to the microenvironment of tumor cells. To test the importance of tissue elasticity in cell culture, primitive neuroectodermal tumor (PNET) stem cells were cultured on soft polyacrylamide (PAA) hydrogel plates that mimics the elasticity of brain tissue compared with PNET on standard polystyrene (PS) plates. We report the molecular profiles of PNET grown on either PAA or PS. Methodology/Principal Findings A whole-genome microarray profile of transcriptional expression between the two culture conditions was performed as a way to probe effects of substrate on cell behavior in culture. The results showed more genes downregulated on PAA compared to PS. This led us to propose microRNA (miRNA) silencing as a potential mechanism for downregulation. Bioinformatic analysis predicted a greater number of miRNA binding sites from the 3' UTR of downregulated genes and identified as specific miRNA binding sites that were enriched when cells were grown on PAA—this supports the hypothesis that tissue elasticity plays a role in influencing miRNA expression. Thus, Dicer was examined to determine if miRNA processing was affected by tissue elasticity. Dicer genes were downregulated on PAA and had multiple predicted miRNA binding sites in its 3' UTR that matched the miRNA binding sites found enriched on PAA. Many differentially regulated genes were found to be present on PS but downregulated on PAA were mapped onto intron sequences. This suggests expression of alternative polyadenylation sites within intron regions that provide alternative 3' UTRs and alternative miRNA binding sites. This results in tissue specific transcriptional downregulation of mRNA in humans by miRNA. We propose a mechanism, driven by the physical characteristics of the microenvironment by which downregulation of genes occur. We found that tissue elasticity-mediated cytokines (TGFβ2 and TNFα) signaling affect expression of ECM proteins. Conclusions Our results suggest that tissue elasticity plays important roles in miRNA expression, which, in turn, regulate tumor growth or tumorigenicity.
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Affiliation(s)
- Long T. Vu
- Neuro-Oncology and Stem Cell Research Laboratory, Center for Neuroscience Research, CHOC Children's Hospital Research Institute, University of California Irvine, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
- Department of Biological Science, California State University, Fullerton, CA, 92834, United States of America
| | - Vic Keschrumrus
- Neuro-Oncology and Stem Cell Research Laboratory, Center for Neuroscience Research, CHOC Children's Hospital Research Institute, University of California Irvine, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
| | - Xi Zhang
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States of America
| | - Jiang F. Zhong
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, United States of America
- * E-mail: (SCL); (JFZ)
| | - Qingning Su
- Bioengineering Research Center, School of Medicine, Shenzhen University, Shenzhen, 518057, Guangdong, China
| | - Mustafa H. Kabeer
- Neuro-Oncology and Stem Cell Research Laboratory, Center for Neuroscience Research, CHOC Children's Hospital Research Institute, University of California Irvine, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
- Department of Pediatric Surgery, CHOC Children's Hospital, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
- Department of Surgery, University of California Irvine School of Medicine, 333 City Blvd. West, Suite 700, Orange, CA 92868, United States of America
| | - William G. Loudon
- Neuro-Oncology and Stem Cell Research Laboratory, Center for Neuroscience Research, CHOC Children's Hospital Research Institute, University of California Irvine, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
- Department of Neurological Surgery, Saint Joseph Hospital, Orange, CA, 92868, United States of America
- Department of Neurological Surgery, University of California Irvine School of Medicine, Orange, CA, 92862, United States of America
| | - Shengwen Calvin Li
- Neuro-Oncology and Stem Cell Research Laboratory, Center for Neuroscience Research, CHOC Children's Hospital Research Institute, University of California Irvine, 1201 West La Veta Ave., Orange, CA, 92868, United States of America
- Department of Neurology, University of California Irvine School of Medicine, Orange, CA, 92697–4292, United States of America
- Department of Biological Science, California State University, Fullerton, CA, 92834, United States of America
- * E-mail: (SCL); (JFZ)
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Integrated analyses of DNA methylation and hydroxymethylation reveal tumor suppressive roles of ECM1, ATF5, and EOMES in human hepatocellular carcinoma. Genome Biol 2014; 15:533. [PMID: 25517360 PMCID: PMC4253612 DOI: 10.1186/s13059-014-0533-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Accepted: 11/06/2014] [Indexed: 12/15/2022] Open
Abstract
Background Differences in 5-hydroxymethylcytosine, 5hmC, distributions may complicate previous observations of abnormal cytosine methylation statuses that are used for the identification of new tumor suppressor gene candidates that are relevant to human hepatocarcinogenesis. The simultaneous detection of 5-methylcytosine and 5-hydroxymethylcytosine is likely to stimulate the discovery of aberrantly methylated genes with increased accuracy in human hepatocellular carcinoma. Results Here, we performed ultra-performance liquid chromatography/tandem mass spectrometry and single-base high-throughput sequencing, Hydroxymethylation and Methylation Sensitive Tag sequencing, HMST-seq, to synchronously measure these two modifications in human hepatocellular carcinoma samples. After identification of differentially methylated and hydroxymethylated genes in human hepatocellular carcinoma, we integrate DNA copy-number alterations, as determined using array-based comparative genomic hybridization data, with gene expression to identify genes that are potentially silenced by promoter hypermethylation. Conclusions We report a high enrichment of genes with epigenetic aberrations in cancer signaling pathways. Six genes were selected as tumor suppressor gene candidates, among which, ECM1, ATF5 and EOMES are confirmed via siRNA experiments to have potential anti-cancer functions. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0533-9) contains supplementary material, which is available to authorized users.
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Liu W, Ju Z, Lu Y, Mills GB, Akbani R. A comprehensive comparison of normalization methods for loading control and variance stabilization of reverse-phase protein array data. Cancer Inform 2014; 13:109-17. [PMID: 25374453 PMCID: PMC4213190 DOI: 10.4137/cin.s13329] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2013] [Revised: 07/07/2014] [Accepted: 07/07/2014] [Indexed: 11/25/2022] Open
Abstract
Loading control (LC) and variance stabilization of reverse-phase protein array (RPPA) data have been challenging mainly due to the small number of proteins in an experiment and the lack of reliable inherent control markers. In this study, we compare eight different normalization methods for LC and variance stabilization. The invariant marker set concept was first applied to the normalization of high-throughput gene expression data. A set of “invariant” markers are selected to create a virtual reference sample. Then all the samples are normalized to the virtual reference. We propose a variant of this method in the context of RPPA data normalization and compare it with seven other normalization methods previously reported in the literature. The invariant marker set method performs well with respect to LC, variance stabilization and association with the immunohistochemistry/florescence in situ hybridization data for three key markers in breast tumor samples, while the other methods have inferior performance. The proposed method is a promising approach for improving the quality of RPPA data.
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Affiliation(s)
- Wenbin Liu
- Department of Bioinformatics and Computational Biology, Unit 1410, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhenlin Ju
- Department of Bioinformatics and Computational Biology, Unit 1410, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yiling Lu
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rehan Akbani
- Department of Bioinformatics and Computational Biology, Unit 1410, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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25
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Panova M, Johansson T, Canbäck B, Bentzer J, Rosenblad MA, Johannesson K, Tunlid A, André C. Species and gene divergence in Littorina snails detected by array comparative genomic hybridization. BMC Genomics 2014; 15:687. [PMID: 25135785 PMCID: PMC4148934 DOI: 10.1186/1471-2164-15-687] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2014] [Accepted: 08/11/2014] [Indexed: 12/11/2022] Open
Abstract
Background Array comparative genomic hybridization (aCGH) is commonly used to screen different types of genetic variation in humans and model species. Here, we performed aCGH using an oligonucleotide gene-expression array for a non-model species, the intertidal snail Littorina saxatilis. First, we tested what types of genetic variation can be detected by this method using direct re-sequencing and comparison to the Littorina genome draft. Secondly, we performed a genome-wide comparison of four closely related Littorina species: L. fabalis, L. compressa, L. arcana and L. saxatilis and of populations of L. saxatilis found in Spain, Britain and Sweden. Finally, we tested whether we could identify genetic variation underlying “Crab” and “Wave” ecotypes of L. saxatilis. Results We could reliably detect copy number variations, deletions and high sequence divergence (i.e. above 3%), but not single nucleotide polymorphisms. The overall hybridization pattern and number of significantly diverged genes were in close agreement with earlier phylogenetic reconstructions based on single genes. The trichotomy of L. arcana, L. compressa and L. saxatilis could not be resolved and we argue that these divergence events have occurred recently and very close in time. We found evidence for high levels of segmental duplication in the Littorina genome (10% of the transcripts represented on the array and up to 23% of the analyzed genomic fragments); duplicated genes and regions were mostly the same in all analyzed species. Finally, this method discriminated geographically distant populations of L. saxatilis, but we did not detect any significant genome divergence associated with ecotypes of L. saxatilis. Conclusions The present study provides new information on the sensitivity and the potential use of oligonucleotide arrays for genotyping of non-model organisms. Applying this method to Littorina species yields insights into genome evolution following the recent species radiation and supports earlier single-gene based phylogenies. Genetic differentiation of L. saxatilis ecotypes was not detected in this study, despite pronounced innate phenotypic differences. The reason may be that these differences are due to single-nucleotide polymorphisms. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-687) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marina Panova
- Department of Biological and Environmental Sciences - Tjärnö, Gothenburg University, Gothenburg, Sweden.
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Rudnick PA, Wang X, Yan X, Sedransk N, Stein SE. Improved normalization of systematic biases affecting ion current measurements in label-free proteomics data. Mol Cell Proteomics 2014; 13:1341-51. [PMID: 24563535 DOI: 10.1074/mcp.m113.030593] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Normalization is an important step in the analysis of quantitative proteomics data. If this step is ignored, systematic biases can lead to incorrect assumptions about regulation. Most statistical procedures for normalizing proteomics data have been borrowed from genomics where their development has focused on the removal of so-called 'batch effects.' In general, a typical normalization step in proteomics works under the assumption that most peptides/proteins do not change; scaling is then used to give a median log-ratio of 0. The focus of this work was to identify other factors, derived from knowledge of the variables in proteomics, which might be used to improve normalization. Here we have examined the multi-laboratory data sets from Phase I of the NCI's CPTAC program. Surprisingly, the most important bias variables affecting peptide intensities within labs were retention time and charge state. The magnitude of these observations was exaggerated in samples of unequal concentrations or "spike-in" levels, presumably because the average precursor charge for peptides with higher charge state potentials is lower at higher relative sample concentrations. These effects are consistent with reduced protonation during electrospray and demonstrate that the physical properties of the peptides themselves can serve as good reporters of systematic biases. Between labs, retention time, precursor m/z, and peptide length were most commonly the top-ranked bias variables, over the standardly used average intensity (A). A larger set of variables was then used to develop a stepwise normalization procedure. This statistical model was found to perform as well or better on the CPTAC mock biomarker data than other commonly used methods. Furthermore, the method described here does not require a priori knowledge of the systematic biases in a given data set. These improvements can be attributed to the inclusion of variables other than average intensity during normalization.
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Affiliation(s)
- Paul A Rudnick
- Mass Spectrometry Data Center, National Institute of Standards and Technology, Gaithersburg, Maryland
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27
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Jellen LC, Lu L, Wang X, Unger EL, Earley CJ, Allen RP, Williams RW, Jones BC. Iron deficiency alters expression of dopamine-related genes in the ventral midbrain in mice. Neuroscience 2013; 252:13-23. [PMID: 23911809 DOI: 10.1016/j.neuroscience.2013.07.058] [Citation(s) in RCA: 43] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2013] [Revised: 07/24/2013] [Accepted: 07/24/2013] [Indexed: 12/01/2022]
Abstract
A clear link exists between iron deficiency (ID) and nigrostriatal dopamine malfunction. This link appears to play an important role in at least restless legs syndrome (RLS) if not several other neurological diseases. Yet, the underlying mechanisms remain unclear. The effects of ID on gene expression in the brain have not been studied extensively. Here, to better understand how exactly ID alters dopamine functioning, we investigated the effects of ID on gene expression in the brain, seeking to identify any potential transcription-based mechanisms. We used six strains of recombinant inbred mice (BXD type) known to differ in susceptibility to ID in the brain. Upon weaning, we subjected mice from each strain to either an iron-deficient or iron-adequate diet. After 100 days of dietary treatment, we measured the effects of ID on gene expression in the ventral midbrain, a region containing the substantia nigra. The substantia nigra is the base of the nigrostriatal dopamine pathway and a region particularly affected by iron loss in RLS. We screened for ID-induced changes in expression, including changes in that of both iron-regulating and dopamine-related genes. Results revealed a number of expression changes occurring in ID, with large strain-dependent differences in the genes involved and number of expression changes occurring. In terms of dopamine-related genes, results revealed ID-induced expression changes in three genes with direct ties to nigrostriatal dopamine functioning, two of which have never before been implicated in an iron-dopamine pathway. These were stromal cell-derived factor 1 (Cxcl12, or SDF-1), a ferritin regulator and potent dopamine neuromodulator, and hemoglobin, beta adult chain 1 (Hbb-b1), a gene recently shown to play a functional role in dopaminergic neurons. The extent of up-regulation of these genes varied by strain. This work not only demonstrates a wide genetic variation in the transcriptional response to ID in the brain, but also reveals two novel biochemical pathways by which iron may potentially alter dopamine function.
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Affiliation(s)
- L C Jellen
- Neuroscience Institute, The Pennsylvania State University, University Park, PA, USA
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Kumar P, Dezso Z, MacKenzie C, Oestreicher J, Agoulnik S, Byrne M, Bernier F, Yanagimachi M, Aoshima K, Oda Y. Circulating miRNA biomarkers for Alzheimer's disease. PLoS One 2013; 8:e69807. [PMID: 23922807 PMCID: PMC3726785 DOI: 10.1371/journal.pone.0069807] [Citation(s) in RCA: 265] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 06/12/2013] [Indexed: 12/13/2022] Open
Abstract
A minimally invasive diagnostic assay for early detection of Alzheimer's disease (AD) is required to select optimal patient groups in clinical trials, monitor disease progression and response to treatment, and to better plan patient clinical care. Blood is an attractive source for biomarkers due to minimal discomfort to the patient, encouraging greater compliance in clinical trials and frequent testing. MiRNAs belong to the class of non-coding regulatory RNA molecules of ∼22 nt length and are now recognized to regulate ∼60% of all known genes through post-transcriptional gene silencing (RNAi). They have potential as useful biomarkers for clinical use because of their stability and ease of detection in many tissues, especially blood. Circulating profiles of miRNAs have been shown to discriminate different tumor types, indicate staging and progression of the disease and to be useful as prognostic markers. Recently their role in neurodegenerative diseases, both as diagnostic biomarkers as well as explaining basic disease etiology has come into focus. Here we report the discovery and validation of a unique circulating 7-miRNA signature (hsa-let-7d-5p, hsa-let-7g-5p, hsa-miR-15b-5p, hsa-miR-142-3p, hsa-miR-191-5p, hsa-miR-301a-3p and hsa-miR-545-3p) in plasma, which could distinguish AD patients from normal controls (NC) with >95% accuracy (AUC of 0.953). There was a >2 fold difference for all signature miRNAs between the AD and NC samples, with p-values<0.05. Pathway analysis, taking into account enriched target mRNAs for these signature miRNAs was also carried out, suggesting that the disturbance of multiple enzymatic pathways including lipid metabolism could play a role in AD etiology.
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Affiliation(s)
- Pavan Kumar
- Eisai Inc, Biomarkers and Personalized Medicine Core Function Unit, Eisai Product Creation Systems, Andover, Massachusetts, United States of America.
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Uszczyńska B, Zyprych-Walczak J, Handschuh L, Szabelska A, Kaźmierczak M, Woronowicz W, Kozłowski P, Sikorski MM, Komarnicki M, Siatkowski I, Figlerowicz M. Analysis of boutique arrays: a universal method for the selection of the optimal data normalization procedure. Int J Mol Med 2013; 32:668-84. [PMID: 23857190 DOI: 10.3892/ijmm.2013.1443] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Accepted: 05/28/2013] [Indexed: 11/06/2022] Open
Abstract
DNA microarrays, which are among the most popular genomic tools, are widely applied in biology and medicine. Boutique arrays, which are small, spotted, dedicated microarrays, constitute an inexpensive alternative to whole-genome screening methods. The data extracted from each microarray-based experiment must be transformed and processed prior to further analysis to eliminate any technical bias. The normalization of the data is the most crucial step of microarray data pre-processing and this process must be carefully considered as it has a profound effect on the results of the analysis. Several normalization algorithms have been developed and implemented in data analysis software packages. However, most of these methods were designed for whole-genome analysis. In this study, we tested 13 normalization strategies (ten for double-channel data and three for single-channel data) available on R Bioconductor and compared their effectiveness in the normalization of four boutique array datasets. The results revealed that boutique arrays can be successfully normalized using standard methods, but not every method is suitable for each dataset. We also suggest a universal seven-step workflow that can be applied for the selection of the optimal normalization procedure for any boutique array dataset. The described workflow enables the evaluation of the investigated normalization methods based on the bias and variance values for the control probes, a differential expression analysis and a receiver operating characteristic curve analysis. The analysis of each component results in a separate ranking of the normalization methods. A combination of the ranks obtained from all the normalization procedures facilitates the selection of the most appropriate normalization method for the studied dataset and determines which methods can be used interchangeably.
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Affiliation(s)
- Barbara Uszczyńska
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznań, Poland
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Calciano M, Lemarié JC, Blondiaux E, Einstein R, Fehlbaum-Beurdeley P. A predictive microarray-based biomarker for early detection of Alzheimer’s disease intended for clinical diagnostic application. Biomarkers 2013; 18:264-72. [DOI: 10.3109/1354750x.2013.773083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Gao F, Xia Y, Wang J, Luo H, Gao Z, Han X, Zhang J, Huang X, Yao Y, Lu H, Yi N, Zhou B, Lin Z, Wen B, Zhang X, Yang H, Wang J. Integrated detection of both 5-mC and 5-hmC by high-throughput tag sequencing technology highlights methylation reprogramming of bivalent genes during cellular differentiation. Epigenetics 2013; 8:421-30. [PMID: 23502161 DOI: 10.4161/epi.24280] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
5-methylcytosine (5-mC) can be oxidized to 5-hydroxymethylcytosine (5-hmC). Genome-wide profiling of 5-hmC thus far indicates 5-hmC may not only be an intermediate form of DNA demethylation but could also constitute an epigenetic mark per se. Here we describe a cost-effective and selective method to detect both the hydroxymethylation and methylation status of cytosines in a subset of cytosines in the human genome. This method involves the selective glucosylation of 5-hmC residues, short-Sequence tag generation and high-throughput sequencing. We tested this method by screening H9 human embryonic stem cells and their differentiated embroid body cells, and found that differential hydroxymethylation preferentially occurs in bivalent genes during cellular differentiation. Especially, our results support hydroxymethylation can regulate key transcription regulators with bivalent marks through demethylation and affect cellular decision on choosing active or inactive state of these genes upon cellular differentiation. Future application of this technology would enable us to uncover the status of methylation and hydroxymethylation in dynamic biological processes and disease development in multiple biological samples.
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Affiliation(s)
- Fei Gao
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Yudong Xia
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Junwen Wang
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Huijuan Luo
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Zhaowei Gao
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Xu Han
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Juyong Zhang
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Xiaojun Huang
- College of Life Sciences; Wuhan University; Wuhan, China
| | - Yu Yao
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Hanlin Lu
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Na Yi
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Baojin Zhou
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Zhilong Lin
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Bo Wen
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Xiuqing Zhang
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Huanming Yang
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China
| | - Jun Wang
- Science & Technology Department; BGI-Shenzhen; Shenzhen, China; Department of Biology; University of Copenhagen; Copenhagen, Denmark; King Abdulaziz University; Jeddah, Saudi Arabia; The Novo Nordisk Foundation Center for Basic Metabolic Research; University of Copenhagen; Copenhagen, Denmark
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Coex-Rank: An approach incorporating co-expression information for combined analysis of microarray data. J Integr Bioinform 2012; 9:208. [PMID: 22842118 DOI: 10.2390/biecoll-jib-2012-208] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2012] [Revised: 05/19/2012] [Accepted: 07/30/2012] [Indexed: 02/06/2023] Open
Abstract
Microarrays have been widely used to study differential gene expression at the genomic level. They can also provide genome-wide co-expression information. Biologically related datasets from independent studies are publicly available, which requires robust combined approaches for integration and validation. Previously, meta-analysis has been adopted to solve this problem. As an alternative to meta-analysis, for microarray data with high similarity in biological experimental design, a more direct combined approach is possible. Gene-level normalization across datasets is motivated by the different scale and distribution of data due to separate origins. However, there has been limited discussion about this point in the past. Here we describe a combined approach for microarray analysis, including gene-level normalization and Coex-Rank approach. After normalization, a linear modeling process is used to identify lists of differentially expressed genes. The Coex-Rank approach incorporates co-expression information into a rank-aggregation procedure. We applied this computational approach to our data, which illustrated an improvement in statistical power and a complementary advantage of the Coex-Rank approach from a biological perspective. Our combined approach for microarray data analysis (Coex-rank) is based on normalization, which is naturally driven. The Coex-rank process not only takes advantage of merging the power of multiple methods regarding normalization but also assists in the discovery of functional clusters of genes.
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Jellen LC, Unger EL, Lu L, Williams RW, Rousseau S, Wang X, Earley CJ, Allen RP, Miles MF, Jones BC. Systems genetic analysis of the effects of iron deficiency in mouse brain. Neurogenetics 2012; 13:147-57. [PMID: 22457016 DOI: 10.1007/s10048-012-0321-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2011] [Accepted: 03/10/2012] [Indexed: 01/16/2023]
Abstract
Iron regulation in the brain is both necessary and highly complex. Too little or too much iron can compromise neurological function, yet we still do not know all of the regulatory processes. In our research, we seek to identify genes and gene networks underlying individual differences in brain iron regulation. To this end, we fed mice from 20+ inbred strains a diet low in iron from weaning to 4 months of age. At sacrifice, we measured iron content in the ventral midbrain (VMB). The VMB contains the substantia nigra, a region particularly vulnerable to iron imbalance. The results showed high, inter-strain variability in dietary iron reduction, from almost no loss to more than 40 % vs. control. When we performed quantitative trait loci (QTL) analysis, we observed a significant area on chromosome 2. Within this QTL, we selected glial high-affinity glutamate transporter 1 (Glt1) as the leading candidate. Expression of this gene is both correlated with VMB iron and is also cis-modulated by local sequence variants that segregate in the BXD family. VMB expression differences of Glt1 in six strains covary with differential susceptibility to VMB iron loss.
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Affiliation(s)
- Leslie C Jellen
- Intercollege Graduate Degree Program in Neuroscience, The Pennsylvania State University, University Park, PA 16802, USA
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Wang D, Cheng L, Zhang Y, Wu R, Wang M, Gu Y, Zhao W, Li P, Li B, Zhang Y, Wang H, Huang Y, Wang C, Guo Z. Extensive up-regulation of gene expression in cancer: the normalised use of microarray data. MOLECULAR BIOSYSTEMS 2012; 8:818-27. [DOI: 10.1039/c2mb05466c] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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35
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Shaw GTW, Shih ESC, Chen CH, Hwang MJ. Preservation of ranking order in the expression of human Housekeeping genes. PLoS One 2011; 6:e29314. [PMID: 22216246 PMCID: PMC3245260 DOI: 10.1371/journal.pone.0029314] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2011] [Accepted: 11/24/2011] [Indexed: 01/26/2023] Open
Abstract
Housekeeping (HK) genes fulfill the basic needs for a cell to survive and function properly. Their ubiquitous expression, originally thought to be constant, can vary from tissue to tissue, but this variation remains largely uncharacterized and it could not be explained by previously identified properties of HK genes such as short gene length and high GC content. By analyzing microarray expression data for human genes, we uncovered a previously unnoted characteristic of HK gene expression, namely that the ranking order of their expression levels tends to be preserved from one tissue to another. Further analysis by tensor product decomposition and pathway stratification identified three main factors of the observed ranking preservation, namely that, compared to those of non-HK (NHK) genes, the expression levels of HK genes show a greater degree of dispersion (less overlap), stableness (a smaller variation in expression between tissues), and correlation of expression. Our results shed light on regulatory mechanisms of HK gene expression that are probably different for different HK genes or pathways, but are consistent and coordinated in different tissues.
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Affiliation(s)
- Grace T. W. Shaw
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Edward S. C. Shih
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan
| | - Chun-Houh Chen
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Ming-Jing Hwang
- Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
- Chemical Biology and Molecular Biophysics Program, Taiwan International Graduate Program, Institute of Biological Chemistry, Academia Sinica, Taipei, Taiwan
- * E-mail:
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36
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Landfors M, Philip P, Rydén P, Stenberg P. Normalization of high dimensional genomics data where the distribution of the altered variables is skewed. PLoS One 2011; 6:e27942. [PMID: 22132175 PMCID: PMC3222656 DOI: 10.1371/journal.pone.0027942] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2011] [Accepted: 10/28/2011] [Indexed: 11/19/2022] Open
Abstract
Genome-wide analysis of gene expression or protein binding patterns using different array or sequencing based technologies is now routinely performed to compare different populations, such as treatment and reference groups. It is often necessary to normalize the data obtained to remove technical variation introduced in the course of conducting experimental work, but standard normalization techniques are not capable of eliminating technical bias in cases where the distribution of the truly altered variables is skewed, i.e. when a large fraction of the variables are either positively or negatively affected by the treatment. However, several experiments are likely to generate such skewed distributions, including ChIP-chip experiments for the study of chromatin, gene expression experiments for the study of apoptosis, and SNP-studies of copy number variation in normal and tumour tissues. A preliminary study using spike-in array data established that the capacity of an experiment to identify altered variables and generate unbiased estimates of the fold change decreases as the fraction of altered variables and the skewness increases. We propose the following work-flow for analyzing high-dimensional experiments with regions of altered variables: (1) Pre-process raw data using one of the standard normalization techniques. (2) Investigate if the distribution of the altered variables is skewed. (3) If the distribution is not believed to be skewed, no additional normalization is needed. Otherwise, re-normalize the data using a novel HMM-assisted normalization procedure. (4) Perform downstream analysis. Here, ChIP-chip data and simulated data were used to evaluate the performance of the work-flow. It was found that skewed distributions can be detected by using the novel DSE-test (Detection of Skewed Experiments). Furthermore, applying the HMM-assisted normalization to experiments where the distribution of the truly altered variables is skewed results in considerably higher sensitivity and lower bias than can be attained using standard and invariant normalization methods.
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Affiliation(s)
- Mattias Landfors
- Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
- Division of Clinical Bacteriology, Umeå University, Umeå, Sweden
- Department of Mathematics and Mathematical Statistics, Umeå University, Umeå, Sweden
| | - Philge Philip
- Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
- Department of Molecular Biology, Umeå University, Umeå, Sweden
| | - Patrik Rydén
- Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
- Department of Mathematics and Mathematical Statistics, Umeå University, Umeå, Sweden
- * E-mail: (PR); (PS)
| | - Per Stenberg
- Computational Life Science Cluster (CLiC), Umeå University, Umeå, Sweden
- Department of Molecular Biology, Umeå University, Umeå, Sweden
- * E-mail: (PR); (PS)
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Hsieh WP, Chu TM, Lin YM, Wolfinger RD. Kernel density weighted loess normalization improves the performance of detection within asymmetrical data. BMC Bioinformatics 2011; 12:222. [PMID: 21631915 PMCID: PMC3118355 DOI: 10.1186/1471-2105-12-222] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2010] [Accepted: 06/01/2011] [Indexed: 01/02/2023] Open
Abstract
Background Normalization of gene expression data has been studied for many years and various strategies have been formulated to deal with various types of data. Most normalization algorithms rely on the assumption that the number of up-regulated genes and the number of down-regulated genes are roughly the same. However, the well-known Golden Spike experiment presents a unique situation in which differentially regulated genes are biased toward one direction, thereby challenging the conclusions of previous bench mark studies. Results This study proposes two novel approaches, KDL and KDQ, based on kernel density estimation to improve upon the basic idea of invariant set selection. The key concept is to provide various importance scores to data points on the MA plot according to their proximity to the cluster of the null genes under the assumption that null genes are more densely distributed than those that are differentially regulated. The comparison is demonstrated in the Golden Spike experiment as well as with simulation data using the ROC curves and compression rates. KDL and KDQ in combination with GCRMA provided the best performance among all approaches. Conclusions This study determined that methods based on invariant sets are better able to resolve the problem of asymmetry. Normalization, either before or after expression summary for probesets, improves performance to a similar degree.
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Affiliation(s)
- Wen-Ping Hsieh
- Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan.
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38
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Extensive increase of microarray signals in cancers calls for novel normalization assumptions. Comput Biol Chem 2011; 35:126-30. [PMID: 21704257 DOI: 10.1016/j.compbiolchem.2011.04.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2011] [Revised: 04/21/2011] [Accepted: 04/21/2011] [Indexed: 01/11/2023]
Abstract
When using microarray data for studying a complex disease such as cancer, it is a common practice to normalize data to force all arrays to have the same distribution of probe intensities regardless of the biological groups of samples. The assumption underlying such normalization is that in a disease the majority of genes are not differentially expressed genes (DE genes) and the numbers of up- and down-regulated genes are roughly equal. However, accumulated evidences suggest gene expressions could be widely altered in cancer, so we need to evaluate the sensitivities of biological discoveries to violation of the normalization assumption. Here, we analyzed 7 large Affymetrix datasets of pair-matched normal and cancer samples for cancers collected in the NCBI GEO database. We showed that in 6 of these 7 datasets, the medians of perfect match (PM) probe intensities increased in cancer state and the increases were significant in three datasets, suggesting the assumption that all arrays have the same median probe intensities regardless of the biological groups of samples might be misleading. Then, we evaluated the effects of three currently most widely used normalization algorithms (RMA, MAS5.0 and dChip) on the selection of DE genes by comparing them with LVS which relies less on the above-mentioned assumption. The results showed using RMA, MAS5.0 and dChip may produce lots of false results of down-regulated DE genes while missing many up-regulated DE genes. At least for cancer study, normalizing all arrays to have the same distribution of probe intensities regardless of the biological groups of samples might be misleading. Thus, most current normalizations based on unreliable assumptions may distort biological differences between normal and cancer samples. The LVS algorithm might perform relatively well due to that it relies less on the above-mentioned assumption. Also, our results indicate that genes may be widely up-regulated in most human cancer.
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McCormick KP, Willmann MR, Meyers BC. Experimental design, preprocessing, normalization and differential expression analysis of small RNA sequencing experiments. SILENCE 2011; 2:2. [PMID: 21356093 PMCID: PMC3055805 DOI: 10.1186/1758-907x-2-2] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2010] [Accepted: 02/28/2011] [Indexed: 01/30/2023]
Abstract
Prior to the advent of new, deep sequencing methods, small RNA (sRNA) discovery was dependent on Sanger sequencing, which was time-consuming and limited knowledge to only the most abundant sRNA. The innovation of large-scale, next-generation sequencing has exponentially increased knowledge of the biology, diversity and abundance of sRNA populations. In this review, we discuss issues involved in the design of sRNA sequencing experiments, including choosing a sequencing platform, inherent biases that affect sRNA measurements and replication. We outline the steps involved in preprocessing sRNA sequencing data and review both the principles behind and the current options for normalization. Finally, we discuss differential expression analysis in the absence and presence of biological replicates. While our focus is on sRNA sequencing experiments, many of the principles discussed are applicable to the sequencing of other RNA populations.
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Affiliation(s)
- Kevin P McCormick
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, DE 19711, USA
| | - Matthew R Willmann
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Blake C Meyers
- Department of Plant and Soil Sciences and Delaware Biotechnology Institute, University of Delaware, Newark, DE 19711, USA
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40
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Chatziioannou AA, Kanaris I, Doukas C, Moulos P, Kolisis FN, Maglogiannis I. GRISSOM platform: enabling distributed processing and management of biological data through fusion of grid and web technologies. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE : A PUBLICATION OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY 2011; 15:83-92. [PMID: 21078581 DOI: 10.1109/titb.2010.2092784] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Transcriptomic technologies have a critical impact in the revolutionary changes that reshape biological research. Through the recruitment of novel high-throughput instrumentation and advanced computational methodologies, an unprecedented wealth of quantitative data is produced. Microarray experiments are considered high-throughput, both in terms of data volumes (data intensive) and processing complexity (computationally intensive). In this paper, we present grids for in silico systems biology and medicine (GRISSOM), a web-based application that exploits GRID infrastructures for distributed data processing and management, of DNA microarrays (cDNA, Affymetrix, Illumina) through a generic, consistent, computational analysis framework. GRISSOM performs versatile annotation and integrative analysis tasks, through the use of third-party application programming interfaces, delivered as web services. In parallel, by conforming to service-oriented architectures, it can be encapsulated in other biomedical processing workflows, with the help of workflow enacting software, like Taverna Workbench, thus rendering access to its algorithms, transparent and generic. GRISSOM aims to set a generic paradigm of efficient metamining that promotes translational research in biomedicine, through the fusion of grid and semantic web computing technologies.
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41
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Swiezewski S, Liu F, Magusin A, Dean C. Cold-induced silencing by long antisense transcripts of an Arabidopsis Polycomb target. Nature 2010; 462:799-802. [PMID: 20010688 DOI: 10.1038/nature08618] [Citation(s) in RCA: 604] [Impact Index Per Article: 43.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2009] [Accepted: 10/30/2009] [Indexed: 01/20/2023]
Abstract
Transcription in eukaryotic genomes generates an extensive array of non-protein-coding RNA, the functional significance of which is mostly unknown. We are investigating the link between non-coding RNA and chromatin regulation through analysis of FLC - a regulator of flowering time in Arabidopsis and a target of several chromatin pathways. Here we use an unbiased strategy to characterize non-coding transcripts of FLC and show that sense/antisense transcript levels correlate in a range of mutants and treatments, but change independently in cold-treated plants. Prolonged cold epigenetically silences FLC in a Polycomb-mediated process called vernalization. Our data indicate that upregulation of long non-coding antisense transcripts covering the entire FLC locus may be part of the cold-sensing mechanism. Induction of these antisense transcripts occurs earlier than, and is independent of, other vernalization markers and coincides with a reduction in sense transcription. We show that addition of the FLC antisense promoter sequences to a reporter gene is sufficient to confer cold-induced silencing of the reporter. Our data indicate that cold-induced FLC antisense transcripts have an early role in the epigenetic silencing of FLC, acting to silence FLC transcription transiently. Recruitment of the Polycomb machinery then confers the epigenetic memory. Antisense transcription events originating from 3' ends of genes might be a general mechanism to regulate the corresponding sense transcription in a condition/stage-dependent manner.
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42
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Noriega NC, Kohama SG, Urbanski HF. Gene expression profiling in the rhesus macaque: methodology, annotation and data interpretation. Methods 2009; 49:42-9. [PMID: 19467334 PMCID: PMC2739830 DOI: 10.1016/j.ymeth.2009.05.008] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2009] [Accepted: 05/18/2009] [Indexed: 12/12/2022] Open
Abstract
Gene microarray analyses represent potentially effective means for high-throughput gene expression profiling in non-human primates. In the companion article, we emphasize effective experimental design based on the in vivo physiology of the rhesus macaque, whereas this article emphasizes considerations for gene annotation and data interpretation using gene microarray platforms from Affymetrix. Initial annotation of the rhesus genome array was based on Affymetrix human GeneChips. However, annotation revisions improve the precision with which rhesus transcripts are identified. Annotation of the rhesus GeneChip is under continuous revision with large percentages of probesets under multiple annotation systems having undergone multiple reassignments between March 2007 and November 2008. It is also important to consider that quantitation and comparison of gene expression levels across multiple chips requires appropriate normalization. External corroboration of microarray results using PCR-based methodology also requires validation of appropriate internal reference genes for normalization of expression values. Many tools are now freely available to aid investigators with microarray normalization and selection of internal reference genes to be used for independent corroboration of microarray results.
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Affiliation(s)
- Nigel C Noriega
- Division of Neuroscience, Oregon National Primate Research Center, 505 NW 185th Avenue, Beaverton, OR 97006, USA.
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