Effect of population size on the estimation of QTL: a test using resistance to barley stripe rust

The limited population sizes used in many quantitative trait locus (QTL) detection experiments can lead to underestimation of QTL number, overestimation of QTL effects, and failure to quantify QTL interactions. We used the barley/barley stripe rust pathosystem to evaluate the effect of population size on the estimation of QTL parameters. We generated a large (n=409) population of doubled haploid lines derived from the cross of two inbred lines, BCD47 and Baronesse. This population was evaluated for barley stripe rust severity in the Toluca Valley, Mexico, and in Washington State, USA, under field conditions. BCD47 was the principal donor of resistance QTL alleles, but the susceptible parent also contributed some resistance alleles. The major QTL, located on the long arm of chromosome 4H, close to the Mlo gene, accounted for up to 34% of the phenotypic variance. Subpopulations of different sizes were generated using three methods—resampling, selective genotyping, and selective phenotyping—to evaluate the effect of population size on the estimation of QTL parameters. In all cases, the number of QTL detected increased with population size. QTL with large effects were detected even in small populations, but QTL with small effects were detected only by increasing population size. Selective genotyping and/or selective phenotyping approaches could be effective strategies for reducing the costs associated with conducting QTL analysis in large populations. The method of choice will depend on the relative costs of genotyping versus phenotyping. Electronic Supplementary Material Supplementary material is available for this article at     

Quantitative trait locus study design from an information perspective

We examine the efficiency of different genotyping and phenotyping strategies in inbred line crosses from an information perspective. This provides a mathematical framework for the statistical aspects of QTL experimental design, while guiding our intuition. Our central result is a simple formula that quantifies the fraction of missing information of any genotyping strategy in a backcross. It includes the special case of selectively genotyping only the phenotypic extreme individuals. The formula is a function of the square of the phenotype and the uncertainty in our knowledge of the genotypes at a locus. This result is used to answer a variety of questions. First, we examine the cost-information trade-off varying the density of markers and the proportion of extreme phenotypic individuals genotyped. Then we evaluate the information content of selective phenotyping designs and the impact of measurement error in phenotyping. A simple formula quantifies the information content of any combined phenotyping and genotyping design. We extend our results to cover multigenotype crosses, such as the F(2) intercross, and multiple QTL models. We find that when the QTL effect is small, any contrast in a multigenotype cross benefits from selective genotyping in the same manner as in a backcross. The benefit remains in the presence of a second unlinked QTL with small effect (explaining <20% of the variance), but diminishes if the second QTL has a large effect. Software for performing power calculations for backcross and F(2) intercross incorporating selective genotyping and marker spacing is available from http://www.biostat.ucsf.edu/sen.     

基于选择基因型对数量性状进行关联分析

数量性状的遗传分析可以通过＂选择基因型＂的方式完成。本文提出了一个利用极端样本来对数量性状位点（QTL）进行关联分析的统计量T。统计量T比较上极端群体样本中具有纯合子标记的性状值差异。通过计算机模拟考察了无关联情形时T的分布和Ⅰ型错误率,结果表明,在各种样本选择策略下,T的分布近似于χ^2-分布,Ⅰ型错误率接近设定的显著性水平。同时,考察了各种遗传模型下不同遗传率,不同样本大小,及不同样本选择阈值对T的统计功效的影响,结果表明,T的功效随着标记和QTL间连锁不平衡程度的增强及遗传率和样本大小的增大而增大,当样本选择阈值更严格时,功效也越大。     

Simultaneous detection and fine mapping of quantitative trait loci in mice using heterogeneous stocks

We describe a method to simultaneously detect and fine map quantitative trait loci (QTL) that is especially suited to the mapping of modifier loci in mouse mutant models. The method exploits the high level of historical recombination present in a heterogeneous stock (HS), an outbred population of mice derived from known founder strains. The experimental design is an F(2) cross between the HS and a genetically distinct line, such as one carrying a knockout or transgene. QTL detection is performed by a standard genome scan with approximately 100 markers and fine mapping by typing the same animals using densely spaced markers over those candidate regions detected by the scan. The analysis uses an extension of the dynamic-programming technique employed previously to fine map QTL in HS mice. We show by simulation that a QTL accounting for 5% of the total variance can be detected and fine mapped with >50% probability to within 3 cM by genotyping approximately 1500 animals.     

Identification and dissection of a complex DNA repair sensitivity phenotype in Baker's yeast

Complex traits typically involve the contribution of multiple gene variants. In this study, we took advantage of a high-density genotyping analysis of the BY (S288c) and RM strains of Saccharomyces cerevisiae and of 123 derived spore progeny to identify the genetic loci that underlie a complex DNA repair sensitivity phenotype. This was accomplished by screening hybrid yeast progeny for sensitivity to a variety of DNA damaging agents. Both the BY and RM strains are resistant to the ultraviolet light–mimetic agent 4-nitroquinoline 1-oxide (4-NQO); however, hybrid progeny from a BY×RM cross displayed varying sensitivities to the drug. We mapped a major quantitative trait locus (QTL), RAD5, and identified the exact polymorphism within this locus responsible for 4-NQO sensitivity. By using a backcrossing strategy along with array-assisted bulk segregant analysis, we identified one other locus, MKT1, and a QTL on Chromosome VII that also link to the hybrid 4-NQO–sensitive phenotype but confer more minor effects. This work suggests an additive model for sensitivity to 4-NQO and provides a strategy for mapping both major and minor QTL that confer background-specific phenotypes. It also provides tools for understanding the effect of genetic background on sensitivity to genotoxic agents.     

A Triad of Highly Divergent Polymeric Immunoglobulin Receptor (PIGR) Haplotypes with Major Effect on IgA Concentration in Bovine Milk

The aim of this study was to determine a genetic basis for IgA concentration in milk of Bos taurus. We used a Holstein-Friesian x Jersey F2 crossbred pedigree to undertake a genome-wide search for QTL influencing IgA concentration and yield in colostrum and milk. We identified a single genome-wide significant QTL on chromosome 16, maximising at 4.8 Mbp. The polymeric immunoglobulin receptor gene (PIGR) was within the confidence interval of the QTL. In addition, mRNA expression analysis revealed a liver PIGR expression QTL mapping to the same locus as the IgA quantitative trait locus. Sequencing and subsequent genotyping of the PIGR gene revealed three divergent haplotypes that explained the variance of both the IgA QTL and the PIGR expression QTL. Genetic selection based on these markers will facilitate the production of bovine herds producing milk with higher concentrations of IgA.     

Mapping of a quantitative trait locus for beef marbling on bovine chromosome 9 in purebred Japanese black cattle

The goal of this study is to detect quantitative trait loci (QTL) for carcass traits applicable for a DNA-based breeding system in a Japanese Black cattle population. A purebred paternal half-sib family from a commercial line composed of 65 steers was initially analyzed using 188 informative microsatellites giving a 16-cM average interval covering 29 autosomes. A significant QTL for marbling was detected in the centromeric portion of bovine chromosome (BTA) 9. After additional marker genotyping across a larger sample size composed of 169 individuals, this locus was refined to a 20-cM confidence interval between microsatellites BM1227 (24 cM) and DIK2741 (50 cM) at a 1% chromosome-wise threshold. The allele substitution effect between Q and q for a beef marbling standard score (1 to 12 range) on BTA9 was 1.0 (5.7% of total phenotypic variance in QTL contribution in this family). This result provides a primary platform for a marker-assisted selection system of the beef marbling trait within the Japanese Black (Wagyu) cattle population.     

Power of different sampling strategies to detect quantitative trait loci variance effects

Summary Many studies have shown that segregating quantitative trait loci (QTL) can be detected via linkage to genetic markers. Power to detect a QTL effect on the trait mean as a function of the number of individuals genotyped for the marker is increased by selectively genotyping individuals with extreme values for the quantitative trait. Computer simulations were employed to study the effect of various sampling strategies on the statistical power to detect QTL variance effects. If only individuals with extreme phenotypes for the quantitative trait are selected for genotyping, then power to detect a variance effect is less than by random sampling. If 0.2 of the total number of individuals genotyped are selected from the center of the distribution, then power to detect a variance effect is equal to that obtained with random selection. Power to detect a variance effect was maximum when 0.2 to 0.5 of the individuals selected for genotyping were selected from the tails of the distribution and the remainder from the center.     

Optimal sampling of a population to determine QTL location, variance, and allelic number

In a population intended for breeding and selection, questions of interest relative to a specific segregating QTL are the variance it generates in the population, and the number and effects of its alleles. One approach to address these questions is to extract several inbreds from the population and use them to generate multiple mapping families. Given random sampling of parents, sampling strategy may be an important factor determining the power of the analysis and its accuracy in estimating QTL variance and allelic number. We describe appropriate multiple-family QTL mapping methodology and apply it to simulated data sets to determine optimal sampling strategies in terms of family number versus family size. Genomes were simulated with seven chromosomes, on which 107 markers and six QTL were distributed. The total heritability was 0.60. Two to ten alleles were segregating at each QTL. Sampling strategies ranged from sampling two inbreds and generating a single family of 600 progeny to sampling 40 inbreds and generating 40 families of 15 progeny each. Strategies involving only one to five families were subject to variation due to the sampling of inbred parents. For QTL where more than two alleles were segregating, these strategies did not sample QTL alleles representative of the original population. Conversely, strategies involving 30 or more parents were subject to variation due to sampling of QTL genotypes within the small families obtained. Given these constraints, greatest QTL detection power was obtained for strategies involving five to ten mapping families. The most accurate estimation of the variance generated by the QTL, however, was obtained with strategies involving 20 or more families. Finally, strategies with an intermediate number of families best estimated the number of QTL alleles. We conclude that no overall optimal sampling strategy exists but that the strategy adopted must depend on the objective.Communicated by P. Langridge     

Mapping the dominant wound healing and soft tissue regeneration QTL in MRL × CAST

We have used a mouse ear punch model and the QTL (quantitative trait loci) mapping technique to identify genes that are responsible for soft tissue regeneration. In the early studies, we have identified several QTL and have shown that the inheritance of ear healing was additive in one cross (MRL × SJL), and recessive in another cross (DBA × 129). Because CAST mice are genetically distinct and have a different genetic background, CAST would facilitate the identification of common and novel QTL when crossed with common inbred lines. We made a cross between super healer MRL and poor healer CAST and collected ear punch phenotype and marker genotype data from F₂. Ear punch healing exhibited a dominant mode of inheritance in this cross. There were three main QTL on Chromosomes 4, 9, and 17, and two suggestive QTL on Chromosomes 1 (new) and 7. Taken together, these QTL accounted for about 29% of total F₂ variance of MRL × CAST. Compared with another study using the same cross, we found a totally different set of QTL. Two QTL interactions were identified by a full QTL model: Chromosomes 4 × 17 and 9 × 17; the latter reached to a statistical level at p < 0.05. These interactions explained about 4% of the F₂ phenotypic variance. We conclude that soft tissue regeneration is controlled by multiple genes and locus vs. locus interactions. This work was supported by Assistance Award No. DAMD17-99-1-9571. The U.S. Army Medical Research Acquisition Activity, Fort Detrick, MD, is the awarding and administering acquisition office. The information contained in this publication does not necessarily reflect the position or policy of the U.S. Government and no official endorsement should be inferred.     

Improving quantitative trait loci mapping resolution in experimental crosses by the use of genotypically selected samples

One of the key factors contributing to the success of a quantitative trait locus (QTL) mapping experiment is the precision with which QTL positions can be estimated. We show, using simulations, that QTL mapping precision for an experimental cross can be increased by the use of a genotypically selected sample of individuals rather than an unselected sample of the same size. Selection is performed using a previously described method that optimizes the complementarity of the crossover sites within the sample. Although the increase in precision is accompanied by a decrease in QTL detection power at markers distant from QTL, only a modest increase in marker density is needed to obtain equivalent power over the whole map. Selected samples also show a slight reduction in the number of false-positive QTL. We find that two features of selected samples independently contribute to these effects: an increase in the number of crossover sites and increased evenness in crossover spacing. We provide an empirical formula for crossover enrichment in selected samples that is useful in experimental design and data analysis. For QTL studies in which the phenotyping is more of a limiting factor than the generation of individuals and the scoring of genotypes, selective sampling is an attractive strategy for increasing genome-wide QTL map resolution.     

Speed-mapping quantitative trait loci using microarrays

We developed a rapid, economical method for high-resolution quantitative trait locus (QTL) mapping using microarrays for selective genotyping of pooled DNA samples. We generated 21,207 F2 flies from two inbred Drosophila melanogaster strains with known QTLs affecting lifespan, and hybridized DNA pools of young and old flies to microarrays. We used changes of gene frequency of 2,326 single-feature polymorphisms (SFPs) to map previously identified and additional QTLs affecting lifespan.     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

Power calculations for selective genotyping in QTL mapping in backcross mice

Selective genotyping concerns the genotyping of a portion of individuals chosen on the basis of their phenotypic values. Often individuals are selected for genotyping from the high and low extremes of the phenotypic distribution. This procedure yields savings in cost and time by decreasing the total number of individuals genotyped. Previous work by Darvasi et al. (1993) has shown that the power to detect a QTL by genotyping 40-50 % of a population is roughly equivalent to genotyping the entire sample. However, these power studies have not accounted for different strategies of analysing the data when phenotypes of individuals in the middle are excluded, nor have they investigated the genome-wide type I error rate under these different strategies or different selection percentages. Further, these simulation studies have not considered markers over the entire genome. In this paper, we present simulation studies of power for the maximum likelihood approach to QTL mapping by Lander & Botstein (1989) in the context of selective genotyping. We calculate the power of selectively genotyping the individuals from the middle of the phenotypic distribution when performing QTL mapping over the whole mouse genome.     

水稻条纹叶枯病抗性位点的检测和效应分析

利用111个家系组成的热研2号(Oryza sativa subsp. japonica ‘Reyan2’)/ Mi lyang23(Oryza sativa subsp. indica ‘Mi lyang23’)重组自交系(recombinant inbred l ines, RIL)群体(F7), 采用重病区田间自然接种方法, 以病情指数作为条纹叶枯病的表型值, 鉴定了2个亲本及111个RIL家系对条纹叶枯病的抗性。使用QTL Cartographer 软件复合区间作图法, 对水稻(Oryza a sativa)条纹叶枯病抗性基因进行了QTL分析。结果检测到2个抗水稻条纹叶枯病的QTL, 分别位于第2和第11染色体上, 其中第11染色体上的QTL贡献率为19.58%, 表明这是一个主效的QTL, 该QTL及其附近的分子标记, 可以用于水稻条纹叶枯病抗性分子标记辅助育种。     

Comparative analysis of haplotype association mapping algorithms

Background  

Finding the genetic causes of quantitative traits is a complex and difficult task. Classical methods for mapping quantitative trail loci (QTL) in miceuse an F2 cross between two strains with substantially different phenotype and an interval mapping method to compute confidence intervals at each position in the genome. This process requires significant resources for breeding and genotyping, and the data generated are usually only applicable to one phenotype of interest. Recently, we reported the application of a haplotype association mapping method which utilizes dense genotyping data across a diverse panel of inbred mouse strains and a marker association algorithm that is independent of any specific phenotype. As the availability of genotyping data grows in size and density, analysis of these haplotype association mapping methods should be of increasing value to the statistical genetics community.     

Individual QTLs controlling quantitative variation in blood pressure inherited in a Mendelian mode

We studied three possible genotypes at 10 well-defined blood pressure (BP) QTLs using congenic rat lines. The central question was whether the hypertensive or normotensive allele is dominant, or whether there is partial dominance. The congenic strains were employed to investigate the BP effects of alleles originating from normotensive rats in the background of hypertensive Dahl salt-sensitive (DSS) rats. The normotensive alleles at eight QTLs were fully dominant over DSS alleles, which we tentatively interpreted as indicating that DSS rats incurred a loss of function at these loci and that the QTLs produced BP-reducing agents. In contrast, the normotensive allele of only one QTL was recessive over its DSS counterpart, implying a gain of function at this QTL or a null allele involved in generating a BP-elevating agent. Only one locus, C17QTL, had alleles exhibiting partial dominance. These estimates of dominance differ considerably from those obtained by QTL analysis in a F2 cross. This disagreement demonstrates the importance of establishing a cause-effect relationship between a QTL and its phenotypic effect via congenic strains. The dominance relationships suggest pertinent strategies for gene identification and pharmaceutical intervention.     

Mapping of a Quantitative Trait Locus for Beef Marbling on Bovine Chromosome 9 in Purebred Japanese Black Cattle

The goal of this study is to detect quantitative trait loci (QTL) for carcass traits applicable for a DNA-based breeding system in a Japanese Black cattle population. A purebred paternal half-sib family from a commercial line composed of 65 steers was initially analyzed using 188 informative microsatellites giving a 16-cM average interval covering 29 autosomes. A significant QTL for marbling was detected in the centromeric portion of bovine chromosome (BTA) 9. After additional marker genotyping across a larger sample size composed of 169 individuals, this locus was refined to a 20-cM confidence interval between microsatellites BM1227 (24 cM) and DIK2741 (50 cM) at a 1% chromosome-wise threshold. The allele substitution effect between Q and q for a beef marbling standard score (1 to 12 range) on BTA9 was 1.0 (5.7% of total phenotypic variance in QTL contribution in this family). This result provides a primary platform for a marker-assisted selection system of the beef marbling trait within the Japanese Black (Wagyu) cattle population.     

Optimal sibship selection for genotyping in quantitative trait locus linkage analysis

In this paper we present a novel method for selecting optimally informative sibships of any size for quantitative trait locus (QTL) linkage analysis. The method allocates a quantitative index of potential informativeness to each sibship on the basis of observed trait scores and an assumed true QTL model. Any sample of phenotypically screened sibships can therefore be easily rank-ordered for selective genotyping. The quantitative index is the sibship's expected contribution to the non-centrality parameter. This expectation represents the weighted sum of chi(2) test statistics that would be obtained given the observed trait values over all possible sibship genotypic configurations; each configuration is weighted by the likelihood of it occurring given the assumed true genetic model. The properties of this procedure are explored in relation to the accuracy of the assumed true genetic model and sibship size. In comparison to previous methods of selecting phenotypically extreme sibships for genotyping, the proposed method is considerably more efficient and is robust with regard to the specification of the genetic model.     

Genetic architecture for hole-board behaviors across substantial time intervals in young, middle-aged and old mice

A quantitative trait locus (QTL) analysis of behaviors across the life span was conducted in F₂ mice from a C57BL/6J × DBA/2J cross and 22 BXD recombinant inbred (RI) strains. Mice of three age groups were tested in a hole-board apparatus for 3 min on three occasions ∼1 month apart (average age at test 150, 450 and 750 days, ∼400 mice per group, divided equally by sex). Quantitative trait loci with small effect size were found on 11 chromosomes for hole-board activity (Hbact) and hole-board rearing (Hbrear). Analysis of 22 RI strains tested at 150 and 450 days of age found only suggestive linkage, with four QTL for Hbact overlapping with those from the F₂ analysis. There was a significant phenotypic correlation between Hbact and Hbrear (∼0.55–0.69) and substantial commonality among QTL for the two behaviors. QTL analyses of head-pokes (HP) and fecal boli (FB) only identified QTL at the suggestive level of significance. Age accounted for ∼15% of the phenotypic variance (sex ∼3%), and there were genotype by age interactions at ∼25% of the Hbact and Hbrear QTL. Quantitative trait loci for Hbrear were relatively stable across the three measurement occasions (those for Hbact somewhat less so), although mean levels of each index declined markedly comparing the first to subsequent trials. Considered as a whole, the polygenic system influencing exploratory behaviors accounts for approximately the same amount of phenotypic variance as age (within the range studied), is stable across substantial periods of time, and acts, for the most part, independently of age and sex.