Statistical Genetics of Quantitative Traits (eBook)

Linkage, Maps and QTL

Rongling Wu, Changxing Ma, George Casella (Autoren)

eBook Download: PDF

2007 | 2007
XVI, 368 Seiten
Springer New York (Verlag)
978-0-387-68154-2 (ISBN)

Infos

This book introduces the basic concepts and methods that are useful in the statistical analysis and modeling of the DNA-based marker and phenotypic data that arise in agriculture, forestry, experimental biology, and other fields. It concentrates on the linkage analysis of markers, map construction and quantitative trait locus (QTL) mapping, and assumes a background in regression analysis and maximum likelihood approaches. The strength of this book lies in the construction of general models and algorithms for linkage analysis, as well as in QTL mapping in any kind of crossed pedigrees initiated with inbred lines of crops.

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Most traits in nature and of importance to agriculture are quantitatively inherited. These traits are di?cult to study due to the complex nature of their inheritance. However, recent developments of genomic technologies provide a revolutionary means for unraveling the secrets of genetic variation in quantitative traits. Genomic te- nologies allow the molecular characterization of polymorphic markers throughout the entire genome that are then used to identify and map the genes or quantitative trait loci (QTLs) underlying a quantitative trait based on linkage analysis. Statistical analysis is a crucial tool for analyzing genome data, which are now becoming increasingly available for a variety of species, and for giving precise exp- nations regarding genetic variation in quantitative traits occurring among species, populations, families, and individuals. In 1989, Lander and Botstein published a ha- mark methodological paper for interval mapping that enables geneticists to detect and estimate individual QTL that control the phenotype of a trait. Today, interval mappingisanimportantstatisticaltoolforstudyingthegeneticsofquantitativetraits at the molecular level, and has led to the discovery of thousands of QTLs responsible for a variety of traits in plants, animals, and humans. In a recent study published in Science, Li, Zhou, and Sang (2006, 311, 1936-1939) were able to characterize the molecular basis of the reduction of grain shattering - a fundamental selection process for rice domestication - at the detected QTL by interval mapping.

Inhalt

Preface 7
Contents 10
1 Basic Genetics 16
1.1 Introduction 16
1.2 Genes and Chromosomes 16
1.3 Meiosis 17
1.4 Mendel’s Laws 18
1.5 Linkage and Mapping 20
1.6 Interference 23
1.7 Quantitative Genetics 23
1.8 Molecular Genetics 31
1.9 SNP 33
1.10 Exercises 35
1.11 Note 35
2 Basic Statistics 39
2.1 Introduction 39
2.2 Likelihood Estimation 41
2.3 Hypothesis Testing 45
2.4 Exercises 54
3 Linkage Analysis and Map Construction 56
3.1 Introduction 56
3.2 Experimental Design 57
3.3 Mendelian Segregation 58
3.4 Segregation Patterns in a Full-Sib Family 59
3.5 Two-Point Analysis 62
3.6 Three-Point Analysis 69
3.7 Multilocus Likelihood and Locus Ordering 71
3.8 Estimation with Many Loci 74
3.9 Mixture Likelihoods and Order Probabilities 75
3.10 Map Functions 76
3.11 Exercises 82
3.12 Notes: Algorithms and Software for Map Construction 84
4 A General Model for Linkage Analysis in Controlled Crosses 89
4.1 Introduction 89
4.2 Fully Informative Markers: A Diplotype Model 90
4.3 Fully Informative Markers: A Genotype Model 100
4.4 Joint modeling of the Linkage, Parental Diplotype, and Gene Order 103
4.5 Partially Informative Markers 108
4.6 Exercises 111
4.7 Notes 113
5 Linkage Analysis with Recombinant Inbred Lines 119
5.1 Introduction 119
5.2 RILs by Selfing 119
5.3 RILs by Sibling Mating 129
5.4 Bias Reduction 130
5.5 Multiway RILs 132
5.6 Exercises 132
5.7 Note 134
6 Linkage Analysis for Distorted and Misclassified Markers 135
6.1 Introduction 135
6.2 Gametic Differential Viability 135
6.3 Zygotic Differential Viability 144
6.4 Misclassification 146
6.5 Simulation 153
6.6 Exercises 154
7 Special Considerations in Linkage Analysis 156
7.1 Introduction 156
7.2 Linkage Analysis with a Complicated Pedigree 156
7.3 Information Analysis of Dominant Markers 171
7.4 Exercises 179
8 Marker Analysis of Phenotypes 182
8.1 Introduction 182
8.2 QTL Regression Model 183
8.3 Analysis at the Marker 185
8.4 Moving Away from the Marker 192
8.5 Power Calculation 195
8.6 Marker Interaction Analysis 199
8.7 Whole-Genome Marker Analysis 206
8.8 Exercises 209
9 The Structure of QTL Mapping 213
9.1 Introduction 213
9.2 The Mixture Model 214
9.3 Population Genetic Structure of the Mixture Model 217
9.4 Quantitative Genetic Structure of the Mixture Model 218
9.5 Experimental Setting of the Mixture Model 223
9.6 Estimation in the Mixture Model 224
9.7 Computational Algorithms for the Mixture Model 226
9.8 Exercises 231
10 Interval Mapping with Regression Analysis 232
10.1 Introduction 232
10.2 Linear Regression Model 233
10.3 Interval Mapping in the Backcross 233
10.4 Interval Mapping in an F2 239
10.5 Remarks 242
10.6 Exercises 243
11 Interval Mapping by Maximum Likelihood Approach 245
11.1 Introduction 245
11.2 QTL Interval Mapping in a Backcross 246
11.3 Hypothesis Testing 254
11.4 QTL Interval Mapping in an F2 262
11.5 Factors That Affect QTL Detection 270
11.6 Procedures for QTL Mapping 271
11.7 Exercises 275
12 Threshold and Precision Analysis 277
12.1 Introduction 277
12.2 Threshold Determination 278
12.3 Precision of Parameter Estimation 287
12.4 Confidence Intervals for the QTL Location 291
12.5 Exercises 293
13 Composite QTL Mapping 294
13.1 Introduction 294
13.2 Composite Interval Mapping for a Backcross 295
13.3 Composite Interval Mapping for an F2 298
13.4 A Statistical Justification of Composite Interval Mapping 300
13.5 Comparisons Between Composite Interval Mapping and Interval Mapping 305
13.6 Multiple Interval Mapping 308
13.7 Exercises 309
14 QTL Mapping in Outbred Pedigrees 310
14.1 Introduction 310
14.2 A Fixed-Effect Model for a Full-Sib Family 311
14.3 Random-Effect Mapping Model for a Complicated Pedigree 324
14.4 Exercises 332
A General Statistical Results and Algorithms 337
A.1 Likelihood Asymptotics 337
A.2 General Form of the EM Algorithm 338
R Programs 340
B.1 Chapter 2 340
B.2 Chapter 8 342
C References 348
Author Index 360
Subject Index 366

Produkt-Details

• Erscheint lt. Verlag: 17.7.2007
• Reihe/Serie: Statistics for Biology and Health
• Reihe/Serie: Statistics for Biology and Health
• Zusatzinfo: XVI, 368 p.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Theorie / Studium
• Themenwelt: Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Medizin / Pharmazie ► Allgemeines / Lexika
• Themenwelt: Naturwissenschaften ► Biologie ► Biochemie
• Themenwelt: Naturwissenschaften ► Biologie ► Botanik
• Themenwelt: Naturwissenschaften ► Biologie ► Evolution
• Themenwelt: Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Zoologie
• Themenwelt: Technik
• Schlagworte: algorithms • Biology • Genetics • linkage analysis • molecular markers • quantitative trait loci • quantitative traits • Regression Analysis • Statistica • Statistical genetics • Statistics
• ISBN-10: 0-387-68154-X / 038768154X
• ISBN-13: 978-0-387-68154-2 / 9780387681542