Bioinformatics for geneticists

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 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 Genetics in the post-genome era—the role of bioinformatics vi CONTENTS 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 CONTENTS vii 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 6.10 Summary 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 13 137 7 viii CONTENTS 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 CONTENTS ix 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 x CONTENTS Chapter 16 Proteomic Informatics 345 J´erˆome Wojcik and Alexandre Hamburger 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 354 16.7 Analysing interaction networks 355 16.8 Cell pathways 356 16.9 Prediction of protein networks 359 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 368 Acknowledgements 369 References 369 Chapter 17 Concluding Remarks: Final Thoughts and Future Trends 373 Michael R. Barnes and Ian C. Gray 17.1 How many genes? 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