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《连锁分析与基因定位（英文版）》建立在作者十多年科研和教学的基础之上，《连锁分析与基因定位（英文版）》可分为三部分。第1章为第一部分，介绍遗传研究群体，主要内容包括常见群体类型、基因型数据的初步整理和分析、基因效应和遗传方差的定义和计算、单环境和多环境表型观测值的方差分析、以及基因型值和遗传力的估计等内容。第2~3章为第二部分，介绍双亲群体连锁分析和遗传图谱构建，主要内容包括世代转移矩阵、两个座位上基因型的理论频率、两个基因座位间重组率的估算、作图函数和遗传图谱构建算法等内容。第4~10章为第三部分，介绍数量性状基因的作图原理和方法，主要内容包括单标记分析、简单区间作图、完备区间作图方法、上位型互作、与环境互作的QTL作图，以及有选择群体、自然群体、无性系杂交群体和多亲本群体的基因定位等内容。

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精彩书评

是植物遗传学、作物遗传育种领域非常好的参考书

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精彩书摘

Chapter 1 Populations in Genetic Studies
　　The population is a set of individuals sharing more or less common characteristics or properties. Population in biology can include all living individuals on the earth as far as the ecological system is concerned. It can also be referred to as all living indi-viduals of one biological species， such as populations of human beings， animals， plants， microbiology， etc. More often， one biological population consists of indi-viduals of one species living in specific areas or societies. As far as genetics is con-cerned， the population is much smaller， where the individuals are more closely related by co-ancestry or relationship by relatives， and therefore sharing more common characteristics. The genetic population can be any race of one biological species， any variety with genetic variation， or the progenies after sexual or asexual propagation using some individuals as parents. Individuals or lines included in one genetic population normally have clear relationships or kinship， but also are different or differ both phenotypically and genetically. For any genetic study， one or some-times several populations are needed.
　　A number of different genotypes have to be included in one genetic population. Many factors can affect population architecture， such as mating systems， the number of parental lines， and population size. Developing the most suitable popu-lations is fundamental to most genetic studies. Population genetics is concerned with gene frequency and genotypic frequency in the genetic populations， how these fre-quencies change from the parental generation to progeny generation taking mating system， mutation， selection， random drift， etc. into consideration， and what effects the changes will make on each population. The number of alleles together with their frequencies at each locus， and the number of genotypes together with their fre-quencies are major parameters characterizing the population structure (Wang， 2017; Hartl and Clark， 2007; Hartl and Jones， 2005; Falconer and Mackay， 1996; Crow and Kimura， 1970). This chapter begins with mating designs and various types of genetic populations， followed by the structure of commonly used populations， collection and preliminary analysis of genotypic data， collection and analysis of variance (ANOVA) on phenotypic data， and estimation of variance components， heritability， and genotypic values.
　　1.1 Commonly Used Populations in Genetic Studies
　　1.1.1 Bi-Parental Populations
　　Various mating designs have been proposed and widely used in genetic studies (Wang， 2017; Bernardo， 2010; Lynch and Walsh， 1998). Populations derived from two homozygous parental lines (also called pure lines or fixed lines) are mostly used in plant genetic studies since the rediscovery of Mendel’s hybridization experiments in garden peas in 1900. The bi-parental mating design begins with two pure lines showing the obvious difference in one or several phenotypic traits. Hybridization is made between the two parents (represented by P1 and P2) to generate their F1 hybrid. Selfing of the F1 hybrid generates the segregating population which is called F2; hybridization between the F1 hybrid and its two parents generates the segregating populations which are called P1BC1F1 if backcrossed with P1， and P2BC1F1 if backcrossed with P2. Selfing and backcrossing may be repeatedly applied in F2， P1BC1F1， and P2BC1F1 so as to have more advanced generations. Recombination inbred lines (RILs) are formed after several rounds of repeated selfing. However， pure lines， which are called the doubled haploid (DH) lines， can also be generated from F1， P1BC1F1， or P2BC1F1 through one generation by DH technology. Figure 1.1 shows 20 bi-parental populations which are commonly used in genetic studies in plants， together with chromosomal segment substitution lines (CSSL) after repeated backcrossing and selfing， and the nested association mapping (NAM) population between several parents and one common parent.
　　FIG. 1.1 – Biparental populations and their derivative relationship in genetic studies in plants.
　　At one polymorphism locus (no matter whether it is a marker or a gene)， assume parent P1 carries allele A， parent P2 carries allele a， and the genotypes of two parents are AA and aa， respectively. When selection and random drift due to the limited population size are not considered， the two alleles have equal frequency， i.e.， 0.5， in selfing， repeated selfing， and DH populations starting from the F1 hybrid. Each generation of backcrossing reduces the frequency of the non-recurrent parent allele by half. Based on the frequency of allele A， i.e.， fA， the 20 biparental populations shown in figure 1.1 fall into five classes.
　　(1) fA = 0.875. Following two generations of backcrossing with parent P1， the fre-quency of allele a is one-quarter of the frequency in F1， i.e.， 0.125， and the frequency of allele A is equal to 0.875 in P1BC2F1. Selfing， repeated selfing， and DH popul

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Contents
Preface III
CHAPTER 1 PopulationsinGeneticStudies 1
1.1 CommonlyUsedPopulationsinGeneticStudies 2
1.1.1 Bi-ParentalPopulations 2
1.1.2 Multi-ParentalPopulations 5
1.1.3 Considerations in Developing Genetic Populations 9
1.2 PreliminaryAnalysisofGenotypicData 12
1.2.1 CollectionandCodingofGenotypicData 12
1.2.2 Gene Frequency and Genotypic Frequency 17
1.2.3 FitnessTestonGenotypicFrequencies 18
1.3 GeneticEffectandGeneticVariance 20
1.3.1 Calculation of Population Mean and Phenotypic Variance 20
1.3.2 One-Locus Additive and Dominance Model 23
1.3.3 Population Mean and Genetic Variance at One Locus 24
1.4 ANOVAonSingleEnvironmentTrials 27
1.4.1 Linear Decomposition on Phenotypic Observation 27
1.4.2 Decomposition of Sum of Squares of Phenotypic Deviations 28
1.4.3 Single Environmental ANOVA on Rice Grain Length 31
1.5 ANOVAonMulti-EnvironmentTrials 32
1.5.1 Linear Decomposition on Phenotypic Observation 32
1.5.2 Decomposition of Sum of Squares of Phenotypic Deviations 33
1.5.3 Multi-Environmental ANOVA on Rice Grain Length 38
1.6 Estimation of Genotypic Values and the Broad-Sense Heritability 39
1.6.1 Genotypic Values and Broad-Sense Heritability fromSingleEnvironmentalTrials 39
1.6.2 Genotypic Values and Broad-Sense Heritability fromMulti-EnvironmentalTrials 41
1.6.3 Estimation of Genotypic Values Under Heterogeneous Error Variances 42 Exercises 45
CHAPTER 2 Estimation of the Two-Point Recombination Frequencies 51
2.1 GenerationTransitionMatrix 51
2.1.1 Usefulness of the Transition Matrix in Linkage Analysis 51
2.1.2 Transition Matrix of One Generation of Backcrossing 53
2.1.3 Transition Matrix of One Generation of Selfing 55
2.1.4 TransitionMatrixofDoubledHaploid 58
2.1.5 TransitionMatrixofRepeatedSelfing 59
2.1.6 Expression of the Two-Locus Genotypic Frequencies inMatrixFormat 61
2.2 Theoretical Genotypic Frequencies at Two Loci 62
2.2.1 Theoretical Frequencies of 10 Genotypes at Two Loci 62
2.2.2 Theoretical Frequencies of 4 Homozygotes in Permanent Populations 65
2.2.3 Genotypic Frequencies of Two Co-Dominant Loci inTemporaryPopulations 65
2.2.4 Genotypic Frequencies of One Co-Dominant Locus and One Dominant Locus in Temporary Populations 69
2.2.5 Genotypic Frequencies of One Co-Dominant Locus and One Recessive Locus in Temporary Populations 69
2.2.6 Genotypic Frequencies of Two Dominant Loci in Temporary Populations 74
2.2.7 Genotypic Frequencies of One Dominant Locus and One Recessive Locus in Temporary Populations 74
2.2.8 Genotypic Frequencies of Two Recessive Loci in Temporary Populations 77
2.3 Estimation of Two-Point Recombination Frequency 77
2.3.1 Maximum Likelihood Estimation of Recombination FrequencyinDHPopulations 77
2.3.2 General Procedure on the Maximum Likelihood Estimation ofRecombinationFrequency 81
2.3.3 Estimation of Recombination Frequency Between One Co-Dominant and One Dominant Marker in F2 population 86
2.3.4 InitialValuesinNewtonAlgorithm 87
2.3.5 EM Algorithm in Estimating Recombination Frequency in F2 Populations 90
2.3.6 Effects on the Estimation of Recombination Frequency from SegregationDistortion 92
Exercises 95
CHAPTER 3 Three-Point Analysis and Linkage Map Construction 101
3.1 Three-Point Analysis and Mapping Function 102
3.1.1 Genetic Interference and Coefficient of Interference 102
3.1.2 Mapping Function 105
3.2 ConstructionofGeneticLinkageMaps 107
3.2.1 MarkerGroupingAlgorithm 107
3.2.2 MarkerOrderingAlgorithm 111
3.2.3 Use of the k-Optimal Algorithm in Linkage Map Construction 113
3.2.4 RipplingoftheOrderedMarkers 117
3.2.5 IntegrationofMultipleMaps 118
3.3 Comparison of the Recombination Frequency Estimation in Different Populations 121
3.3.1 LOD Score in Testing the Linkage Relationship in Different Populations 121
3.3.2 Accuracy of the Estimated Recombination Frequency 123
3.3.3 Least Population Size to Declare the Significant Linkage RelationshipandCloseLinkage 124
3.4 Linkage Analysis in Random Mating Populations 127
3.4.1 Linkage Dis-Equilibrium in Random Mating Populations 127
3.4.2 Generation Transition Matrix from Diploid Genotypes toHaploidGametes 130
3.4.3 Gametic and Genotypic Frequencies in Populations After SeveralGenerationsofRandomMating 132 Exercises 134
CHAPTER 4 Single Marker Analysis and Simple Interval Mapping 139
4.1 SingleMarkerAnalysis 140
4.1.1 Phenotypic Means of Different Genotypes at One Marker Locus 140
4.1.2 Single Marker Analysis by t-Test in Populations with Two Genotypes 143
4.1.3 Single Marker Analysis by t-Test in Populations with Three Genotypes 146
4.1.4 ANOVA in Single Marker Analysis in Populations with Three Genotypes 150
4.1.5 Likelihood Ratio Test in Single Marker Analysis 151
4.1.6 ProblemswithSingleMarkerAnalysis 153
4.2 SimpleIntervalMapping 154
4.2.1 Frequencies of the QTL Genotypes in a Marker Interval 154
4.2.2 Maximum Likelihood Estimation of Phenotypic Means ofQTLGenotypes 161
4.2.3 TestingfortheExistenceofQTL 166
4.2.4 Estimation

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