DNA Microarrays: Databases and Statistics Part B

486 Pages·2006·13.308 MB·English

by  Kimmel A.R., Oliver B. (eds.)

METHODS IN ENZYMOLOGY
EDITORS-IN-CHIEF
John N. Abelson Melvin I. Simon
DIVISIONOFBIOLOGY
CALIFORNIAINSTITUTEOFTECHNOLOGY
PASADENA,CALIFORNIA
FOUNDING EDITORS
Sidney P. Colowick and Nathan O. Kaplan
Table of Contents
CONTRIBUTORSTOVOLUME411. . . . . . . . . . . . . . . . . ix
VOLUMESINSERIES. . . . . . . . . . . . . . . . . . . . . xiii
1. RNAExtractionforArrays LAKSHMIV.MADABUSI,
GARYJ.LATHAM,AND
BERNARDF.ANDRUSS 1
2. AnalyzingMicro-RNAExpressionUsing TIMOTHYS.DAVISON,
Microarrays CHARLESD.JOHNSON,AND
BERNARDF.ANDRUSS 14
3. TroubleshootingMicroarrayHybridizations BRIANEADS,
AMYCASH,
KEVINBOGART,
JAMESCOSTELLO,AND
JUSTENANDREWS 34
4. UseofExternalControlsinMicroarray IVANAV.YANG 50
Experiments
5. StandardsinGeneExpressionMicroarray MARCSALIT 63
Experiments
6. ScanningMicroarrays:CurrentMethodsand JERILYNA.TIMLIN 79
FutureDirections
7. AnIntroductiontoBioArraySoftware CARLTROEIN,JOHAN
Environment VALLON-CHRISTERSSON,
ANDLAOH.SAAL 99
8. Bioconductor:AnOpenSourceFramework MARKREIMERSAND
forBioinformaticsandComputational VINCENTJ.CAREY 119
Biology
v
vi TABLE OF CONTENTS
9. TM4MicroarraySoftwareSuite ALEXANDERI.SAEED,
NIRMALK.BHAGABATI,
JOHNC.BRAISTED,
WEILIANG,
VASILYSHAROV,
ELEANORA.HOWE,
JIANWEILI,
MATHANGITHIAGARAJAN,
JOSEPHA.WHITE,AND
JOHNQUACKENBUSH 134
10. ClusteringMicroarrayData JEREMYGOLLUBAND
GAVINSHERLOCK 194
11. AnalysisofVarianceofMicroarrayData JULIENF.AYROLESAND
GREGGIBSON 214
12. MicroarrayQualityControl JAMESM.MINOR 233
13. AnalysisofaMultifactorMicroarrayStudy TOMDOWNEY 256
UsingPartekGenomicsSolution
14. StatisticsforChIP-chipandDNase PETERC.SCACHERI,
HypersensitivityExperimentson GREGORYE.CRAWFORD,
NimbleGenArrays ANDSEANDAVIS 270
15. ExtrapolatingTraditionalDNAMicroarray THOMASE.ROYCE,
StatisticstoTilingandProtein JOELS.ROZOWSKY,
MicroarrayTechnologies NICHOLASM.LUSCOMBE,
OLOFEMANUELSSON,
HAIYUANYU,
XIAOWEIZHU,
MICHAELSNYDER,AND
MARKB.GERSTEIN 282
16. RandomDataSetGenerationtoSupport DANIELQ.NAIMAN 312
MicroarrayAnalysis
17. UsingOntologiestoAnnotate PATRICIAL.WHETZEL,
MicroarrayExperiments HELENPARKINSON,AND
CHRISTIANJ.STOECKERT,JR 325
18. InterpretingExperimentalResultsUsing TIMBEISSBARTH 340
GeneOntologies
19. GeneExpressionOmnibus: TANYABARRETTAND
MicroarrayDataStorage,Submission, RONEDGAR 352
Retrieval,andAnalysis
TABLEOFCONTENTS vii
20. DataStorageandAnalysisinArrayExpress ALVISBRAZMA,
MISHAKAPUSHESKY,
HELENPARKINSON,
UGISSARKINS,AND
MOHAMMADSHOJATALAB 370
21. ClusteringMethodsforAnalyzingLarge JE´ROˆMEHENNETINAND
DataSets:GonadDevelopment, MICHELBELLIS 387
AStudyCase
22. VisualizingNetworks GEORGEW.BELLAND
FRANLEWITTER 408
23. RandomForestsforMicroarrays ADELECUTLERAND
JOHNR.STEVENS 422
AUTHORINDEX . . . . . . . . . . . . . . . . . . . . . . 433
SUBJECTINDEX . . . . . . . . . . . . . . . . . . . . . . 461
Contributors to Volume 411
Articlenumbersareinparenthesesandfollowingthenameofcontributors.
Affiliationslistedarecurrent.
JUSTEN ANDREWS (3), Department of AMYCASH(3),DepartmentofBiology,In-
Biology, Indiana University, Blooming- dianaUniversity,Bloomington,Indiana
ton,Indiana
JAMES COSTELLO (3), Drosophila Geno-
BERNARD F. ANDRUSS (1, 2), Asuragen, mics Resource Center, Indiana Univer-
Inc.,Austin,Texas sity,Bloomington,Indiana
JULIEN F. AYROLES (11), Department of GREGORYE. CRAWFORD(14), Department
Genetics, North Carolina State Univer- of Pediatrics, Institute for Genome
sity,Raleigh,NorthCarolina Sciences and Policy, Duke University,
Durham,NorthCarolina
TANYABARRETT(19),NationalCenter for
Biotechnology Information, National ADELECUTLER(23),DepartmentofMathe-
LibraryofMedicine,NationalInstitutes maticsandStatistics,UtahStateUniver-
ofHealth,Bethesda,Maryland sity,Logan,Utah
TIMBEISSBARTH(18),TheWalterandEliza SEANDAVIS(14),CancerGeneticsBranch,
Hall Institute of Medical Research, Bio- NationalHumanGenomeResearchInsti-
informaticsGroup,Victoria,Australia tute,NationalInstitutesofHealth,Bethes-
da,Maryland
GEORGEW.BELL(22),Bioinformaticsand
Research Computing, Whitehead Insti- TIMOTHYS.DAVISON(2),AsuragenDiscov-
tute for Biomedical Research, Cam- eryServices,Asuragen,Inc.,Austin,Texas
bridge,Massachusetts
TOM DOWNEY (13), Partek Incorporated,
MICHELBELLIS(21),CRBM–CNRS,Mont- SaintLouis,Missouri
pellier,France
BRIAN EADS (3),DepartmentofBiology,
NIRMALK.BHAGABATI(9), TheInstitutefor IndianaUniversity,Bloomington,Indiana
GenomicResearch,Rockville,Maryland
RON EDGAR (19), National Center for
KEVIN BOGART(3),DrosophilaGenomics Biotechnology Information, National
Resource Center, Indiana University, LibraryofMedicine,Bethesda,Maryland
Bloomington,Indiana
OLOF EMANUELSSON (15), Department of
JOHN C. BRAISTED (9), The Institute for MolecularBiophysicsand Biochemistry,
GenomicResearch,Rockville,Maryland YaleUniversity,NewHaven,Connecticut
ALVIS BRAZMA (20), European Bioinfor- MARK B. GERSTEIN (15), Department of
maticsInstitute,WellcomeTrustGenome MolecularBiophysicsand Biochemistry,
Campus, Hinxton, Cambridge, United YaleUniversity,NewHaven,Connecticut
Kingdom
GREGGIBSON(11), DepartmentofGenet-
VINCENTJ.CAREY(8),HarvardUniversity, ics, North Carolina State University,
Boston,Massachusetts Raleigh,NorthCarolina
ix
x CONTRIBUTORS TO VOLUME 411
JEREMYGOLLUB*(10),DepartmentofBio- HELENPARKINSON(17,20),EuropeanBio-
chemistry, Stanford University Medical informatics Institute, Wellcome Trust
School,Stanford,California Genome Campus, Hinxton, Cambridge,
UnitedKingdom
JE´ROˆME HENNETIN (21), CRBM–CNRS,
Montpellier,France JOHN QUACKENBUSH (9), Department of
Biostatistics and Computational Biol-
ELEANOR A. HOWE (9), Department of ogy, Dana-Farber Cancer Institute Bos-
Biostatistics and Computational Biol-
ton,Massachusetts
ogy,Dana-FarberCancerInstitute,Bos-
ton,Massachusetts MARKREIMERS(8),NationalCancerInsti-
tute,Bethesda,Maryland
CHARLES D. JOHNSON (2), Asuragen Dis-
covery Services, Asuragen, Inc., Austin, THOMASE. ROYCE(15),PrograminCom-
Texas putational Biology and Bioinformatics,
YaleUniversity,NewHaven,Connecticut
MISHA KAPUSHESKY (20), European Bio-
informatics Institute, Wellcome Trust JOEL S. ROZOWSKY (15), Department of
Genome Campus, Hinxton, Cambridge, MolecularBiophysicsandBiochemistry,
UnitedKingdom YaleUniversity,NewHaven,Connecticut
GAtiRnY,TJe.xLaAsTHAM(1),Asuragen,Inc.,Aus- LAOH.SAAL(7),InstituteforCancerGen-
etics, College of Physicians and Sur-
FRAN LEWITTER (22), Bioinformatics and geons,ColumbiaUniversity,NewYork,
Research Computing, Whitehead Insti- NewYork
tute for Biomedical Research, Cam-
bridge,Massachusetts ALEXANDER I. SAEED (9), Department of
Bioinformatics, The Institute for Geno-
JIANWEI LI (9), The Institute for Genomic micResearch,Rockville,Maryland
Research,Rockville,Maryland
MARC SALIT (5), Chemical Science and
WEILIANG(9),TheInstituteforGenomic Technology Laboratory, National Insti-
Research,Rockville,Maryland tute of Standards and Technology,
Gaithersburg,Maryland
NICHOLAS M. LUSCOMBE (15), European
Bioinformatics Institute,WellcomeTrust UGIS SARKANS (20), European Bioinfor-
Genome Campus, Hinxton, Cambridge, matics Institute, Wellcome Trust Gen-
UnitedKingdom ome Campus, Hinxton, Cambridge,
UnitedKingdom
LAKSHMIV. MADABUSI (1),AsuragenDis-
covery Services, Asuragen, Inc., Austin, PETER C. SCACHERI (14), Department of
Texas Genetics,CaseWesternReserveUniver-
sity,Cleveland,Ohio
JAMESM.MINOR(12),AgilentTechnologies,
Inc.,SantaClara,California VASILY SHAROV (9), The Institute for
GenomicResearch,Rockville,Maryland
DANIEL Q. NAIMAN (16), Department of
Applied Mathematics and Statistics, GAVIN SHERLOCK (10), Department of
Johns Hopkins University, Baltimore, Genetics, Stanford University Medical
Maryland School,Stanford,California
*Currentaffiliation:InconixPharmaceuticals,Inc.,MountainView,California.
CONTRIBUTORSTO VOLUME411 xi
MOHAMMAD SHOJATALAB (20), European JOHAN VALLON-CHRISTERSSON(7),Depart-
BioinformaticsInstitute,WellcomeTrust ment of Oncology, Lund University
Genome Campus, Hinxton, Cambridge, Hospital,Lund,Sweden
UnitedKingdom
PATRICIA L. WHETZEL (17), Department
MICHAEL SNYDER(15),DepartmentofMo- of Genetics, Center for Bioinformatics,
lecular, Cellular, and Developmental University of Pennsylvania School of
Biology, Yale University, New Haven, Medicine,Philadelphia,Pennsylvania
Connecticut
JOSEPHA.WHITE(9),DepartmentofBios-
JOHNR.STEVENS(23),DepartmentofMath- tatistics and Computational Biology,
ematicsandStatistics,UtahStateUniver-
Dana-Farber Cancer Institute, Boston,
sity,Logan,Utah
Massachusetts
CHRISTIANJ. STOECKERT,JR.(17), Depart-
mentofGenetics,CenterforBioinforma- IVANA V. YANG (4), Laboratory of Res-
piratory Biology, National Institute of
tics,UniversityofPennsylvaniaSchoolof
Environmental Health Sciences, Re-
Medicine,Philadelphia,Pennsylvania
searchTrianglePark,NorthCarolina
MATHANGI THIAGARAJAN (9), Department
of Bioinformatics, The Institute for HAIYUANYU(15), DepartmentofMolecu-
GenomicResearch,Rockville,Maryland lar Biophysics and Biochemistry, Yale
University,NewHaven,Connecticut
JERILYNA.TIMLIN(6),BiomolecularAna-
lysis and Imaging, Sandia National La- XIAOWEIZHU(15), Program in Computa-
boratories,Albuquerque,NewMexico tionalBiologyandBioinformatics,Yale
University,NewHaven,Connecticut
CARL TROEIN (7), Computational Biology
and Biological Physics, Department of
Theoretical Physics, Lund University,
Lund,Sweden
[1] RNA EXTRACTIONFORARRAYS 1
[1] RNA Extraction for Arrays
By LAKSHMI V. MADABUSI, GARY J. LATHAM, and
BERNARD F. ANDRUSS
Abstract
DNA microarrays enable insights into global gene expression by
capturing a snapshot of cellular expression levels at the time of sample
collection. Careful RNA handling and extraction are required to preserve
this information properly, ensure sample‐to‐sample reproducibility, and
limit unwanted technical variation in experimental data. This chapter dis-
cusses important considerations for ‘‘array‐friendly’’ sample handling and
processing from biosamples such as blood, formalin‐fixed, paraffin‐
embedded samples, and fresh or flash‐frozen tissues and cells. It also
provides guidelines on RNA quality assessments, which can be used to
validate sample preparation and maximize recovery of relevant biological
information.
Introduction
DNA microarrays have enabled biologists to move from the realm of
studyingonegeneatatimetounderstandinggenome‐widechangesingene
expression. The value of microarray studies has been vetted through nu-
merous studies that have linked abnormal transcript levels with many
different diseases (Archacki and Wang, 2004; Blalock et al., 2004;
Borovecki et al., 2005; Dhanasekaran et al., 2001; Glatt et al., 2005; West
et al., 2001). Because these types of studies will be used increasingly to
create and validate diagnostic and prognostic expression signatures and
tosupporttoxicologicalandfunctionalstudiesthatunderlietheregulatory
filings for new drug submissions, it will become increasingly important to
create standardized and robust methods for sample procurement, sample
processing, anddataanalysis.ThegoalofanyRNAisolationprocedure is
to recover an RNA population that faithfully mirrors the biology of the
sample at the time of collection. Problems associated with the extraction
of biologically representative RNA primarily arise from the susceptibility
of RNAtodegradationbyubiquitousandcatalyticallypotentRNases.For
tissues and cells, protection of RNA has traditionally been accomplished
by immediate lysis using high concentrations of detergents and/or chao-
tropic agents and organic solvents (such as TRI reagent). These methods,
METHODSINENZYMOLOGY,VOL.411 0076-6879/06$35.00
Copyright2006,ElsevierInc.Allrightsreserved. DOI:10.1016/S0076-6879(06)11001-0
2 DNA microarrays, part B [1]
while effective, are complex to use at point of care and suffer from low
samplethroughputandpoorstabilizationofcellularRNAforlongperiods.
Flashfreezingofthesampleinliquidnitrogenandsubsequenttransporta-
tionondryice,althougheffective,areimpracticalinmostclinicalsettings.
Finally,diseasespecimenscanpresentbiohazardriskstotheoperatorand
constrain sample collection, thus limiting the use of best sample handling
and processing practicesand compromising RNA quality.
ThepracticalityandefficacyofRNAstabilizationagentssuchasRNA-
later to preserve the RNA in tissues, cells, and blood are gaining broad
acceptance. Procedures used for collection of samples with RNAlater are
simple and can be carried out in a hospital setting with minimal training.
Thisreagentisaqueousandnontoxicandallowsconvenienttransportation
of samples at ambient temperature. However, RNAlater does not remove
the biohazard risks associated with biosamples, and, as a result, all proper
safety precautions should be observed. It is beyond the scope of this
chaptertoprovidedetailsontherisksassociatedandpreventivemeasures
to be taken when dealing with samples considered to be a biohazard.
Several regulatory agencies offer guidelines on the safety issues and
precautions that need to beaddressed with such samples.
In addition to the handling of biological material, limitations can be
imposed by the large amounts of RNA necessary for microarray experi-
ments.Asaresult,samplessuchastumorbiopsies,formalin‐fixed,paraffin‐
embedded (FFPE)sections, orlasermicrodissectedsamples requireRNA
amplificationtogenerateadequateamountsoflabeledmaterialformicro-
array hybridization. The most popular and best validated approaches for
amplifying RNA are based on the linear RNA amplification method de-
veloped byEberwine(VanGelder,1990).Thistechniquehasbeenwidely
acceptedformicroarrayapplicationsandisknowntopreservetheoriginal
transcriptratiosinthesample(Feldmanetal.,2002;Polaceketal.,2003).In
terms of RNA quality, parameters such as A260:280 measurements and
Agilent RNA integrity number (RIN) are often used to gauge the quality
of samples and predict their suitability for microarray studies. The mini-
mum A260:280 or RIN number suitable for analysis varies by the array
platform, number of replicates, and the experimental questions to be
answered inthe study.
Blood as a Biological Specimen
Blood is a highly desirable biosample for research and clinical studies
for several reasons. First, blood is highly accessible and can be collected
using relatively simple methods. Second, limited infrastructure is required
to draw blood from a large number of patients. Finally, blood circulates