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E-raamat: Microarray Technology Through Applications

Edited by (University of Birmingham, UK)
  • Formaat: 276 pages
  • Ilmumisaeg: 11-Jun-2007
  • Kirjastus: Taylor & Francis Ltd
  • Keel: eng
  • ISBN-13: 9781134182749
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Microarray Technology Through ApplicationsSuurem pilt
  • Formaat: 276 pages
  • Ilmumisaeg: 11-Jun-2007
  • Kirjastus: Taylor & Francis Ltd
  • Keel: eng
  • ISBN-13: 9781134182749
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Microarray Technology Through Applications provides the reader with an understanding, from an applications perspective, of the diverse range of concepts required to master the experimental and data analysis aspects of microarray technology.

The first chapter is a concise introduction to the technology and provides the theoretical background required to understand the subsequent sections. The following chapters are a series of case studies representative of the most general and important applications of microarray technology, including CGH, analysis of gene expression, SNP arrays and protein arrays. The case studies are written by experts in the field and describe prototypic projects, indicating how to generalize the approach to similar studies. There are detailed step-by-step protocols describing the specific experimental and data analysis protocols mentioned in the case study section. There is also information on printing glass DNA microarray slides and data interpretation.



Colour figures and data sets are provided on the website at http://www.garlandscience.com/9780415378536

Arvustused

"With a collection of interesting case studies and a hands-on approach, this survey of experimental and data analysis methods and techniques in microarray technology takes the needs of the novice into consideration along with the curiosity of the practitioner in applications research." Book News Inc

Table 0.1 Key to link cases to protocols and supplementary information
xi
Contributors xiii
Abbreviations xv
Preface xvii
Useful links xix
SECTION 1
1(226)
Introduction to microarray technology
1(52)
Jon L. Hobman
Antony Jones
Chrystala Constantinidou
Introduction to the technology and its applications
1(11)
Microarrays as research tools
1(1)
Arrays and microarrays
2(4)
Principles of DNA array technology
6(1)
Microarrays as tools for biological research applications
7(5)
The design of a microarray
12(1)
Glass slide DNA microarrays
12(6)
The technology
13(1)
Microarray fabrication
13(1)
A typical glass slide microarray transcriptomics experiment
14(1)
Array printing
14(1)
Experimental design
15(1)
Sample preparation
15(1)
Sample labeling, hybridization, and detection
16(1)
Technical challenges
17(1)
Affymetrix microarrays
18(4)
The technology
18(1)
Microarray fabrication
19(1)
Sample labeling, hybridization, and detection
20(1)
Applications
21(1)
Microarray platforms for protein studies and other applications
22(12)
Protein arrays
22(1)
Protein expression arrays (capture arrays) and protein function arrays
23(2)
The technology
25(1)
Microarray fabrication
26(1)
Sample labeling, hybridization, and detection
26(1)
Applications
27(1)
Technical challenges
28(3)
Carbohydrate/glycan arrays
31(1)
The technology
31(1)
Labeling and detection
32(1)
Applications
32(1)
Technical challenges
33(1)
Other array formats
34(1)
Data/image acquisition
34(19)
Image analysis
37(1)
Addressing or gridding
38(1)
Segmentation
38(1)
Measurements: spot intensity and background intensity
39(1)
Quality measures
40(1)
Data storage
40(2)
Acknowledgments
42(1)
References
42(11)
Immunoprecipitation with microarrays to determine the genome-wide binding profile of a DNA-associated protein
53(20)
Joseph T. Wade
Introduction
53(1)
Background
53(4)
Description of ChIP-chip
54(2)
Advantages of ChIP-chip over related techniques
56(1)
Experimental design
57(4)
Immunoprecipitation considerations
57(1)
Microarray considerations
58(1)
Amplification methods
59(1)
Choice of control
60(1)
Data acquisition
61(1)
Theory of data analysis
61(5)
Analysis of data generated using spotted PCR product microarrays
61(1)
Error model
62(1)
Analysis of data generated using tiled oligonucleotide microarrays
63(1)
Accounting for dye bias
64(1)
Alternative analyses
64(1)
Comparing subsets of the genome
64(1)
Identifying specific binding sites
64(1)
Comparing ChIP-chip data for different proteins
65(1)
Data analysis
66(1)
Spotted PCR product microarrays
66(1)
Tiled oligonucleotide microarrays
66(1)
Summary of the results, conclusions and related applications
66(7)
Alternatives to ChIP-chip
68(1)
Techniques related to ChIP-chip
69(1)
References
70(3)
Array-based comparative genomic hybridization as a tool for solving practical biological and medical questions
73(16)
David Blesa
Sandra Rodriguez-Perales
Sara Alvarez
Cristina Largo
Juan C. Cigudosa
Introduction
73(2)
Scientific background
75(1)
Leukemic cells with normal karyotype may show cytogenetically undetectable DNA copy number changes
75(1)
The cloning of a familial translocation associated with renal cell carcinoma
75(1)
Design of experiments
76(3)
Acute myeloid leukemia with normal karyotype
78(1)
Cloning of the translocation t(3;8)(p14.1;q24.32)
79(1)
Data acquisition
79(2)
Acute myeloid leukemia with normal karyotype
79(1)
Cloning of the translocation t(3;8)(p14.1;q24.32)
80(1)
Theory of data analysis
81(1)
Data analysis
82(1)
Summary of the results
83(3)
Acute myeloid leukemia with normal karyotype
83(1)
Cloning of the translocation t(3;8)(p14.1;q24.32)
84(2)
Conclusions and suggestions for the general implementation of the case study
86(3)
Acknowledgments
86(1)
References
87(2)
Use of single nucleotide polymorphism arrays: Design, tools, and applications
89(20)
Mercedes Robledo
Anna Gonzalez-Neira
Joaquin Dopazo
Introduction
89(4)
Direct association approach
91(1)
Indirect association approach
92(1)
Combined approach
93(1)
Scientific background: Essential steps to be considered in the design of the experiment
93(3)
Candidate gene selection
93(1)
Selection criteria for single nucleotide polymorphisms
94(2)
Use of microarray technology: The Illumina platform as an example
96(1)
Tools for data acquisition and data analysis
96(7)
Computational tools for selecting optimal SNPs: two-step protocol
97(3)
A computational tool for SNP genotyping analysis: General software
100(3)
Summary and conclusions
103(6)
Acknowledgments
104(1)
References
104(5)
In vitro analysis of gene expression
109(16)
Donling Zheng
Chrystala Constantinidou
Jon L. Hobman
Steve D. Minchin
Introduction
109(1)
Scientific background
110(1)
Design of the experiment
111(1)
Data acquisition
112(1)
Theory of data analysis
113(1)
Identification of differentially transcribed genes
113(1)
Data analysis
114(5)
Outlier method
115(1)
Standard t-test
115(2)
SAM statistic analysis
117(1)
Operon organization
117(1)
Comparison of the outlier, standard t-test, and SAM methods
118(1)
Summary of results, conclusions, and suggestions for general implementation of the case study
119(6)
Characterization of the CRP regulon by ROMA
119(2)
Comparison of ROMA with in vivo transcriptional profiling
121(1)
Comparison of ROMA with genome sequence searching
121(1)
References
122(3)
The analysis of cellular transcriptional response at the genome level: Two case studies with relevance to bacterial pathogenesis
125(30)
Thomas Carzaniga
Donatella Sarti
Victor Trevino
Christopher Buckley
Mike Salmon
Shabnam Moobed
David Wild
Chrystala Constantinidou
Jon L. Hobman
Gianni Deho
Francesco Falciani
Introduction
125(1)
Scientific background
126(2)
Case study 1: The response of E. coli cells to adaptation to body temperature
126(1)
Case study 2: The response of human intestinal cells to E. coli infection
127(1)
Design of the experiment
128(3)
Case study 1: The response of E. coli cells to adaptation to body temperature
128(1)
Case study 2: The response of human intestinal cells to E. coli infection
128(3)
A description of data analysis procedures
131(3)
Data normalization
131(1)
Identifying differentially expressed genes
132(1)
Data exploration techniques
133(1)
Implementation
134(1)
Data analysis tutorials
134(7)
Case study 1: The response of E. coli cells to adaptation to body temperature
134(3)
Case study 2: The response of human intestinal cells to E. coli infection
137(4)
Results and discussion
141(11)
Case study 1: The response of E. coli cells to adaptation to body temperature
141(7)
Case study 2: The response of human intestinal cells to E. coli infection
148(4)
Conclusions
152(3)
Acknowledgments
152(1)
References
152(3)
Functional annotation of microarray experiments
155(18)
Joaquin Dopazo
Fatima Al-Shahrour
Introduction
155(1)
Scientific background
156(2)
Functional annotation
156(1)
What can be considered a significant functional difference? Statistical approaches and the multiple testing problem
157(1)
Design of the experiment
158(1)
Theory of data analysis
159(2)
Testing unequal distribution of terms between two groups of genes
159(1)
Unsupervised approach
160(1)
Supervised approach
161(1)
Data analysis
161(6)
Functional annotation of a cluster of co-expressing genes
161(5)
Functional annotation of differentially expressed genes
166(1)
Summary of the results, conclusions, and suggestions for the general implementation of the case study
167(6)
Acknowledgments
169(1)
References
169(4)
Microarray technology in agricultural research
173(38)
Ana Conesa
Javier Forment
Jose Gadea
Jeroen van Dijk
Introduction
173(1)
Microarray resources in agricultural research
173(1)
Home-made plant microarrays
173(6)
Construction of cDNA libraries
176(1)
Isolation and partial sequencing of cDNA clones
176(1)
Processing and analysis of EST sequences
176(2)
Generation of the probes by PCR amplification
178(1)
Probe spotting on the glass slides
179(1)
Microarrays and genetically modified organisms
179(7)
Genetically modified crops and their implication for food safety
179(3)
Microarrays as profiling tools for screening GM crops
182(1)
Technical considerations for plant microarrays
183(2)
Transcriptomics in relation to other `-omics' techniques
185(1)
A data analysis example: Time course of gene expression response to stress in transgenic plants
186(15)
Statistical analysis
188(11)
Biological interpretation of gene expression results
199(2)
Concluding remarks
201(10)
References
203(8)
Protein microarrays
211(16)
Nigel J. Saunders
Introduction
211(1)
The uses and application of protein microarrays
211(6)
Antigen-antibody interactions and immunoassays
213(2)
Phage display libraries and protein microarrays
215(1)
Use of protein microarrays to assess arrayed samples
216(1)
Focused functional assays on protein microarrays
217(1)
The practicalities of protein microarrays
217(6)
Slide substrates
217(2)
Detection/labeling systems
219(1)
Data extraction and analysis
219(1)
DNA-protein studies
220(1)
An experimental example of the use of protein microarrays
220(3)
Some summary points
223(1)
Overall concluding remarks
223(4)
References
224(3)
SECTION 2: EXPERIMENTAL PROTOCOLS
227(62)
Manufacturing arrays
Protocol 1: Printing oligonucleotide microarrays
227(4)
Expression profiling
Protocol 2: Extraction of E. coli RNA
231(4)
Protocol 3: Probe labeling
235(6)
Protocol 4: Hybridization and washing
241(6)
Other applications
Protocol 5: ChIP procedure
247(2)
Protocol 6: Array comparative genomic hybridization (CGH)
249(4)
Protocol 7: Run-off microarray analysis of gene expression (ROMA)
253(6)
Protocol 8: Selection and genotyping of single nucleotide polymorphisms
259(2)
APPENDICES
Notes on printing glass DNA microarray slides
261(8)
Antony Jones
Comparative genomics. The nature of CGH analysis and data interpretation
269(16)
Lori A.S. Snyder
Graham Snudden
Nick Haan
Nigel J. Saunders
Useful web links to microarray resources
285(2)
The genes selected for clustering (Chapter 6, Figure 6.4)
287(2)
Index 289


Francesco Falciani, Senior Lecturer in Bioinformatics, School of Biosciences, University of Birmingham, UK
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