Tiling Arrays: Methods and Protocols

238 Pages·2013·5.21 MB·English

by  Christophe Lemetre

Methods in
Molecular Biology 1067
Tin-Lap Lee
Alfred Chun Shui Luk Editors
Tiling Arrays
Methods and Protocols
M M B ™
ETHODS IN OLECULAR IOLOGY
Series Editor
John M. Walker
School of Life Sciences
University of Hertfordshire
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Tiling Arrays
Methods and Protocols
Edited by
Tin-Lap Lee
Reproduction, Endocrinology and Development Program,
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin,
Hong Kong SAR, China
Alfred Chun Shui Luk
Reproduction, Endocrinology and Development Program,
School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin,
Hong Kong SAR, China
Editors
Tin-Lap Lee Alfred Chun Shui Luk
Reproduction, Endocrinology Reproduction, Endocrinology
and Development Program and Development Program
School of Biomedical Sciences School of Biomedical Sciences
The Chinese University of Hong Kong The Chinese University of Hong Kong
Shatin, Hong Kong SAR, China Shatin, Hong Kong SAR, China
ISSN 1064-3745 ISSN 1940-6029 (electronic)
ISBN 978-1-62703-606-1 ISBN 978-1-62703-607-8 (eBook)
DOI 10.1007/978-1-62703-607-8
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Pref ace
With over 23,000 scientifi c publications, microarray technology represents an indispensible
tool in genome discovery and continues to contribute to novel fi ndings along with other
high-throughput technologies. The application of microarrays becomes very popular in
academic labs as well as in clinics and commercial entities. During the last decade, the
design and coverage of microarrays have gone through a drastic development. Conventional
microarrays were largely applied to gene expression study. The density was usually low and
the probes were limited to known annotations, which led to incomplete and biased conclu-
sions. The advent of tiling microarrays not only addressed the weakness of conventional
microarrays but also provided a new avenue for other genomic applications.
Departing from the biased gene-centric probe design approach, probes on tiling micro-
arrays rely purely on genomic DNA sequence information. The probes are evenly distrib-
uted across the nonrepetitive portion of the genome. Commercially available tiling array
platforms offer fl exible designs with a range of probe lengths and spacing options. According
to Gene Expression Omnibus (GEO) at National Center for Biotechnology Information
(NCBI), more than 1,100 tiling microarray platforms are now available for various unbi-
ased genomic discoveries.
Typical tiling microarray applications include transcriptome landscape discovery
through mapping of the entire transcribed populations, identifying protein binding and
methylated regions by chromatin immunoprecipitation (ChIP-chip) and Methylated DNA
immunoprecipitation (MeDIP), and identifying genomic origins of replication. Such versa-
tile and robust nature has contributed signifi cantly in decoding the dark matter in the
genome, which provides supporting evidence of widespread transcription and regulation
events. These include the discovery of novel long noncoding RNAs to the identifi cation of
spatiotemporal patterns of gene expression, to the characterization of the transcriptome in
various developmental stages and models. Despite high-throughput sequencing methods
have recently demonstrated distinct advantages over array-based approaches with regard to
data resolution, the “big data” generated requires steep requirements on computer hard-
ware and complex bioinformatics analysis. Tiling microarrays could fi ll this gap with many
established supporting software. Also, the availability of large tiling array reference datasets
in major public repositories like GEO, ArrayExpress, and The Encyclopedia of DNA
Elements (ENCODE) will allow rapid and straightforward meta-analysis.
This volume focuses on the key applications of tiling microarrays in genomic discovery,
including transcriptional regulation, expression, and genetic and epigenetic regulation.
Given the applications and types of microarray technology become more numerous and
diverse, the limited consensus of how to analyze and interpret the data becomes more
apparent. To cope with such challenging issues, the chapters in the data analysis section
v
vi Preface
cover techniques and skills on tiling microarray data analysis that allow readers to leverage
the power of dataset from novel perspectives and platform-independent tools. It is our
hope that this volume will provide a comprehensive and a down-to-earth approach for
maximizing reader’s knowledge on this topic.
China, People’s Republic Tin-Lap Lee
A lfred Chun Shui Luk
Contents
Preface .................................................................................................................... v
Contributors .................................................................................................................... ix
PART I OVERVIEW
1 A Brief Introduction to Tiling Microarrays: Principles, Concepts,
and Applications ............................................................................................... 3
Christophe Lemetre and Zhengdong D. Zhang
PART II TRANSCRIPTIONAL REGULATION AND EXPRESSION
2 Design of Tiling Arrays and Their Application
to Bacterial Transcriptome Analysis .................................................................. 23
Takeshi Akama, Kazuaki Nakamura, Akito Tanoue, and Koichi Suzuki
3 Transcript Profiling in Arabidopsis with Genome Tiling Microarrays ................. 35
Diana Coman, Wilhelm Gruissem, and Lars Hennig
4 Genome-Wide Analysis of Transcription Factor-Binding Sites
in Skeletal Muscle Cells Using ChIP-Seq .......................................................... 51
Chung-II An and Nobuko Hagiwara
5 Analysis of Allele-Specific Gene Expression Using a Target-O riented
Tiling Microarray Assay .................................................................................... 65
Huiyong Zhang, Xing-Wang Deng, and Lei Li
PART III GENETICS AND EPIGENETICS REGULATION
6 Detection of Epigenetic Alterations Using Tiling Arrays ................................... 79
Hoi-Hung Cheung, Owen M. Rennert, and Tin-Lap Lee
7 Investigating Gene Promoter Methylation in a Mouse Model
of Status Epilepticus .......................................................................................... 87
Suzanne F.C. Miller-Delaney, Sudipto Das, Raymond L. Stallings,
and David C. Henshall
PART IV DATA ANALYSIS
8 Integrative Analysis of ChIP-Chip and ChIP-Seq Dataset ................................. 105
Lihua Julie Zhu
9 HAT: A Novel Statistical Approach to Discover Functional Regions
in the Genome ................................................................................................. 125
Erdogan Taskesen, Bas Wouters, and Ruud Delwel
vii
viii Contents
10 Inference of Alternative Splicing from Tiling Array Data ................................... 143
Johannes Eichner
11 Analysis of In Vivo Occupancy of Aebp1, a Transcription Factor,
Using High Resolution Tiling Array ................................................................. 165
Swati Sinha, Sainitin Donakonda, and Satyanarayana MR Rao
12 Application of the Simple and Efficient Mpeak Modeling
in Binding Peak Identification in ChIP-Chip Studies ........................................ 185
Ming Zheng, Yunmin Li, and Yun-Fai Chris Lau
13 Evaluation of MeDIP-Chip in the Context of Whole-Genome Bisulfite
Sequencing (WGBS-Seq) in Arabidopsis ........................................................... 203
René Wardenaar, Haiyin Liu, Vincent Colot, Maria Colomé-Tatché,
and Frank Johannes
14 Mapping Genomic Features of Tiling Microarray Data by TileMapper .............. 225
Hoi-Hung Cheung, Janek Claus, Sumeeta Singh, Chandan Sastry,
Owen M. Rennert, Wai-Yee Chan, and Tin-Lap Lee
Index ............................................................................................................................... 235
Contributors
TAKESHI AKAMA • Leprosy Research Center, National Institute of Infectious Diseases ,
Tokyo , Japan
CHUNG-IL AN • Division of Cardiovascular Medicine, Department of Internal Medicine ,
University of California, Davis , Davis , CA , USA
WAI-YEE CHAN • Laboratory of Clinical Genomics, Eunice Kennedy Shriver National
Institute of Child Health and Human Development, National Institutes of Health ,
Bethesda, MD, USA
HOI-HUNG CHEUNG • Laboratory of Clinical and Developmental Genomics,
Eunice Kennedy Shriver National Institute of Child Health and Human Development,
National Institutes of Health , Bethesda, MD , USA
JANEK CLAUS • Division of Information Technology , Eunice Kennedy Shriver National
Institute of Child Health and Human Development, National Institutes of Health ,
Bethesda, MD, USA
MARIA COLOMÉ-TATCHÉ • Faculty of Mathematics and Natural Sciences, Groningen
Bioinformatics Centre, University of Groningen , AG Groningen, The Netherlands
VINCENT COLOT • Institut de Biologie de l’Ecole Normale Supérieure, Centre National de
la Recherche Scientifi que (CNRS) UMR8197-Institut National de la Santé et de la
Recherche Médicale (INSERM) , Paris , France
DIANA COMAN • Plant Biotechnology, Department of Biology, ETH Zurich , Zurich,
Switzerland
SUDIPTO DAS • Cancer Genetics, Department of Molecular and Cellular Therapeutics, Royal
College of Surgeons in Ireland, Dublin, Ireland; The National Children’s Research
Centre, Our Lady’s Children’s Hospital, Crumlin, Dublin, Ireland
RUUD DELWEL • Department of Hematology , Erasmus University Medical Center ,
Rotterdam , The Netherlands
XING-WANG DENG • Department of Molecular, Cellular and Developmental Biology,
Yale University , New Haven, CT , USA
SAINITIN DONAKONDA • Biotechnologisches Zentrum, Technische Universität , Dresden,
Germany
JOHANNES EICHNER • Center for Bioinformatics, University of Tuebingen , Tübingen, Germany
WILHELM GRUISSEM • Plant Biotechnology, Department of Biology, ETH Zurich , Zurich,
Switzerland ; Functional Genomics Center Zurich, ETH Zurich , Zurich , Switzerland
NOBUKO HAGIWARA • Division of Cardiovascular Medicine, Department of Internal
Medicine, University of California, Davis , Davis , CA , USA
LARS HENNIG • Plant Biotechnology, Department of Biology, ETH Zurich , Zurich,
Switzerland ; Functional Genomics Center Zurich, ETH Zurich , Zurich , Switzerland ;
Department of Plant Biology and Forest Genetics, Uppsala BioCenter, Swedish University
of Agricultural Sciences and Linnean Center for Plant Biology , Uppsala , Sweden
DAVID C. HENSHALL • Department of Physiology and Medical Physics, The Royal College of
Surgeons in Ireland , Dublin, Ireland
ix