Bioinformatics for Geneticists

CONTENTS
List of contributors xi
Foreword xiii
SECTION I. AN INTRODUCTION TO BIOINFORMATICS FOR THE
GENETICIST 1
Chapter 1 Introduction: The Role of Genetic Bioinformatics 3
Michael R. Barnes and Ian C. Gray
1.1 Introduction 3
1.2 Genetics in the post-genome era — the role of bioinformatics 6
1.3 Knowledge management and expansion 6
1.4 Data management and mining 6
1.5 Genetic study designs 8
1.6 Physical locus analysis 12
1.7 Selecting candidate genes for analysis 14
1.8 Progressing from candidate gene to disease-susceptibility gene 14
1.9 Comparative genetics and genomics 15
1.10 Conclusions 17
References 18
Chapter 2 Internet Resources for the Geneticist 21
Michael R. Barnes and Christopher Southan
2.1 Introduction 22
2.2 Sub-division of biological data on the internet 23
2.3 Searching the internet for genetic information 24
2.4 Which web search engine? 24
2.5 Search syntax: the mathematics of search engine use 26
2.6 Boolean searching 27
2.7 Searching scientific literature — getting to ‘state of the art’ 28
2.8 Searching full-text journals 29
2.9 Searching the heart of the biological internet — sequences and genomic
data 30
2.10 Nucleotide and protein sequence databases 30
2.11 Biological sequence databases — primary and secondary 31
2.12 Conclusions 36
References 37
Chapter 3 Human Genetic Variation: Databases and Concepts 39
Michael R. Barnes
3.1 Introduction 40
3.2 Forms and mechanisms of genetic variation 43
3.3 Databases of human genetic variation 50
3.4 SNP databases 51
3.5 Mutation databases 57
3.6 Genetic marker and microsatellite databases 60
3.7 Non-nuclear and somatic mutation databases 61
3.8 Tools for SNP and mutation visualization — the genomic context 63
3.9 Tools for SNP and mutation visualization — the gene context 63
3.10 Conclusions 67
References 67
Chapter 4 Finding, Delineating and Analysing Genes 71
Christopher Southan
4.1 Introduction 71
4.2 The evidence cascade for gene products 72
4.3 Shortcomings of the standard gene model 75
4.4 Locating known genes on the Golden Path 76
4.5 Gene portal inspection 79
4.6 Locating genes which are not present in the Golden Path 80
4.7 Analysing a novel gene 81
4.8 Comprehensive database searching 88
4.9 Conclusions and prospects 90
References 90
SECTION II. THE IMPACT OF COMPLETE GENOME SEQUENCES
ON GENETICS 93
Chapter 5 Assembling a View of the Human Genome 95
Colin A. Semple
5.1 Introduction 95
5.2 Genomic sequence assembly 98
5.3 Annotation from a distance: the generalities 101
5.4 Annotation up close and personal: the specifics 105
5.5 Annotation: the next generation 113
Acknowledgements 114
References 114
Chapter 6 Mouse and Rat Genome Informatics 119
Judith A. Blake, Janan Eppig and Carol J. Bult
6.1 Introduction 120
6.2 The model organism databases for mouse and rat 122
6.3 Mouse genetic and physical maps 124
6.4 Rat genetic and physical maps 127
6.5 Genome sequence resources 128
6.6 Comparative genomics 131
6.7 From genotype to phenotype 132
6.8 Functional genomics 135
6.9 Rodent disease models 137
137
6.10 Summary
137
Acknowledgements
References 138
Chapter 7 Genetic and Physical Map Resources — An Integrated View 143
Michael R. Barnes
7.1 Introduction 144
7.2 Genetic maps 145
7.3 Physical maps 148
7.4 Physical contig maps 151
7.5 The role of physical and genetic maps in draft sequence curation 152
7.6 The human genome sequence — the ultimate physical map? 153
7.7 QC of genomic DNA — resolution of marker order and gap sizes 154
7.8 Tools and databases for map analysis and integration 155
7.9 Conclusions 159
References 160
SECTION III. BIOINFORMATICS FOR GENETIC STUDY DESIGN 163
Chapter 8 From Linkage Peak to Culprit Gene: Following Up Linkage
Analysis of Complex Phenotypes with Population-based Association Studies 165
Ian C. Gray
8.1 Introduction 165
8.2 Theoretical and practical considerations 166
8.3 A practical approach to locus refinement and candidate gene identification 173
8.4 Conclusion 176
Acknowledgements 176
References 177
Chapter 9 Genetic Studies from Genomic Sequence 179
Michael R. Barnes
9.1 Introduction 180
9.2 Defining the locus 180
9.3 Case study 1: Identification and extraction of a genomic sequence between
two markers 184
9.4 Case study 2: Checking the integrity of a genomic sequence between two
markers 185
9.5 Case study 3: Definition of known and novel genes across a genomic
region 188
9.6 Case study 4: Candidate gene selection — building biological rationale
around genes 190
9.7 Case study 5: Known and novel marker identification 195
9.8 Case study 6: Genetic/physical locus characterization and marker
panel design 199
9.9 Conclusions 201
References 201
Chapter 10 SNP Discovery and PCR-based Assay Design: From In Silico
Data to the Laboratory Experiment 203
Ellen Vieux, Gabor Marth and Pui Kwok
10.1 Introduction 204
10.2 SNP identification 205
10.3 PCR primer design 207
10.4 Broader PCR assay design issues 208
10.5 Primer selection 210
10.6 Problems related to SNP assay validation 212
10.7 Conclusion 213
References 213
Chapter 11 Tools for Statistical Analysis of Genetic Data 217
Aruna Bansal, Peter R. Boyd and Ralph McGinnis
11.1 Introduction 218
11.2 Linkage analysis 218
11.3 Association analysis 223
11.4 Haplotype Reconstruction 226
11.5 Linkage disequilibrium 229
11.6 Quantitative Trait Locus (QTL) mapping in experimental crosses 235
Acknowledgements 240
References 240
SECTION IV. BIOLOGICAL SEQUENCE ANALYSIS AND
CHARACTERIZATION 247
Chapter 12 Predictive Functional Analysis of Polymorphisms:
An Overview 249
Michael R. Barnes
12.1 Introduction 250
12.2 Principles of predictive functional analysis of polymorphisms 252
12.3 The anatomy of promoter regions and regulatory elements 257
12.4 The anatomy of genes 258
12.5 Pseudogenes and regulatory mRNA 264
12.6 Analysis of novel regulatory elements and motifs in nucleotide
sequences 264
12.7 Functional analysis on non-synonymous coding polymorphisms 266
12.8 A note of caution on the prioritization of in silico predictions for further
laboratory investigation 268
12.9 Conclusions 268
References 269
Chapter 13 Functional In Silico Analysis of Non-coding SNPs 273
Thomas Werner
13.1 Introduction 273
13.2 General structure of chromatin-associated DNA 275
13.3 General functions of regulatory regions 276
13.4 Transcription Factor binding sites (TF-sites) 276
13.5 Structural elements 276
13.6 Organizational principles of regulatory regions 277
13.7 RNA processing 279
13.8 SNPs in regulatory regions 279
13.9 Evaluation of non-coding SNPs 280
13.10 SNPs and regulatory networks 281
13.11 SNPs may affect the expression of a gene only in specific tissues 281
13.12 In silico detection and evaluation of regulatory SNPs 281
13.13 Getting promoter sequences 282
13.14 Identification of relevant regulatory elements 283
13.15 Estimation of functional consequences of regulatory SNPs 284
13.16 Conclusion 285
References 285
Chapter 14 Amino Acid Properties and Consequences of Substitutions 289
Matthew J. Betts and Robert B. Russell
14.1 Introduction 291
14.2 Protein features relevant to amino acid behaviour 292
14.3 Amino acid classifications 296
14.4 Properties of the amino acids 298
14.5 Amino acid quick reference 299
14.6 Studies of how mutations affect function 311
14.7 A summary of the thought process 313
References 314
SECTION V. GENETICS/GENOMICS INTERFACES 317
Chapter 15 Gene Expression Informatics and Analysis 319
Antoine H. C. van Kampen, Jan M. Ruijter, Barbera D. C. van Schaik, Huib N.
Caron and Rogier Versteeg
15.1 Introduction 320
15.2 Technologies for the measurement of gene expression 322
15.3 The Cancer Genome Anatomy Project (CGAP) 324
15.4 Processing of SAGE data 325
15.5 Integration of biological databases for the construction of the HTM 334
15.6 The Human Transcriptome Map 336
15.7 Regions of Increased Gene Expression (RIDGES) 339
15.8 Discussion 340
References 341
Chapter 16 Proteomic Informatics 345
J ́ rˆ me Wojcik and Alexandre Hamburger
eo
16.1 Introduction 346
16.2 Proteomic informatics 347
16.3 Experimental workflow: classical proteomics 347
16.4 Protein interaction networks 351
16.5 Building protein interaction networks 354
16.6 False negatives and false positives
16.7 Analysing interaction networks 355
16.8 Cell pathways 356
16.9 Prediction of protein networks
16.10 Assessment and validation of predictions 363
16.11 Exploiting protein networks 366
16.12 Deducing prediction rules from networks 367
16.13 Conclusion
Acknowledgements
References
AM
FL
Y
354
359
368
369
369
Chapter 17 Concluding Remarks: Final Thoughts and Future Trends 373
Michael R. Barnes and Ian C. Gray
17.1 How many genes?
TE
374
17.2 Mapping the genome and gaining a view of the full depth of human
variation
375
17.3 Holistic analysis of complex traits 376
17.4 A final word on bioinformatics
376
Acknowledgements 376
References 376
Appendix I 379
Appendix II 381
Glossary 387
Index 391

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