Quantitative trait locus analysis in crosses between outbred lines with dominance and inbreeding

In an effort to determine the genetic basis of exceptionally large tomato fruits, QTL analysis was performed on a population derived from a cross between the wild species Lycopersicon pimpinellifolium (average fruit weight, 1 g) and the L. esculentum cultivar var. Giant Heirloom, which bears fruit in excess of 1000 g. QTL analysis revealed that the majority (67%) of phenotypic variation in fruit size could be attributed to six major loci localized on chromosomes 1-3 and 11. None of the QTL map to novel regions of the genome-all have been reported in previous studies involving moderately sized tomatoes. This result suggests that no major QTL beyond those already reported were involved in the evolution of extremely large fruit. However, this is the first time that all six QTL have emerged in a single population, suggesting that exceptionally large-fruited varieties, such as Giant Heirloom, are the result of a novel combination of preexisting QTL alleles. One of the detected QTL, fw2.2, has been cloned and exerts its effect on fruit size through global control of cell division early in carpel/fruit development. However, the most significant QTL detected in this study (fw11.3, lcn11.1) maps to the bottom of chromosome 11 and seems to exert its effect on fruit size through control of carpel/locule number. A second major locus, also affecting carpel number (and hence fruit size), was mapped to chromosome 2 (fw2.1, lcn2.1). We propose that these two carpel number QTL correspond to the loci described by early classical geneticists as fasciated (f) and locule number (lc), respectively.     

QTL mapping in outbred half-sib families using Bayesian model selection

In this article, we propose a model selection method, the Bayesian composite model space approach, to map quantitative trait loci (QTL) in a half-sib population for continuous and binary traits. In our method, the identity-by-descent-based variance component model is used. To demonstrate the performance of this model, the method was applied to map QTL underlying production traits on BTA6 in a Chinese half-sib dairy cattle population. A total of four QTLs were detected, whereas only one QTL was identified using the traditional least square (LS) method. We also conducted two simulation experiments to validate the efficiency of our method. The results suggest that the proposed method based on a multiple-QTL model is efficient in mapping multiple QTL for an outbred half-sib population and is more powerful than the LS method based on a single-QTL model.     

Quantitative trait loci mapping in F(2) crosses between outbred lines

We develop a mixed-model approach for QTL analysis in crosses between outbred lines that allows for QTL segregation within lines as well as for differences in mean QTL effects between lines. We also propose a method called "segment mapping" that is based in partitioning the genome in a series of segments. The expected change in mean according to percentage of breed origin, together with the genetic variance associated with each segment, is estimated using maximum likelihood. The method also allows the estimation of differences in additive variances between the parental lines. Completely fixed random and mixed models together with segment mapping are compared via simulation. The segment mapping and mixed-model behaviors are similar to those of classical methods, either the fixed or random models, under simple genetic models (a single QTL with alternative alleles fixed in each line), whereas they provide less biased estimates and have higher power than fixed or random models in more complex situations, i.e., when the QTL are segregating within the parental lines. The segment mapping approach is particularly useful to determining which chromosome regions are likely to contain QTL when these are linked.     

Combined detection and introgression of QTL in outbred populations

Background

Detecting a QTL is only the first step in genetic improvement programs. When a QTL with desirable characteristics is found, e.g. in a wild or unimproved population, it may be interesting to introgress the detected QTL into the commercial population. One approach to shorten the time needed for introgression is to combine both QTL identification and introgression, into a single step. This combines the strengths of fine mapping and backcrossing and paves the way for introgression of desirable but unknown QTL into recipient animal and plant lines.

Methods

The method consisting in combining QTL mapping and gene introgression has been extended from inbred to outbred populations in which QTL allele frequencies vary both in recipient and donor lines in different scenarios and for which polygenic effects are included in order to model background genes. The effectiveness of the combined QTL detection and introgression procedure was evaluated by simulation through four backcross generations.

Results

The allele substitution effect is underestimated when the favourable QTL allele is not fixed in the donor line. This underestimation is proportional to the frequency differences of the favourable QTL allele between the lines. In most scenarios, the estimates of the QTL location are unbiased and accurate. The retained donor chromosome segment and linkage drag are similar to expected values from other published studies.

Conclusions

In general, our results show that it is possible to combine QTL detection and introgression even in outbred species. Separating QTL mapping and introgression processes is often thought to be longer and more costly. However, using a combined process saves at least one generation. With respect to the linkage drag and obligatory drag, the results of the combined detection and introgression scheme are very similar to those of traditional introgression schemes.     

Power of two and three-generation QTL mapping experiments in an outbred population containing full-sib or half-sib families

QTL mapping experiments involve many animals to be genotyped and performance tested. Consequently, experimental designs need to be optimized to minimize the costs of data collection and genotyping. The present study has analyzed the power and efficiency of experiments with two or three-generation family structures containing full-sib families, half-sib families, or both. The focus was on data from one outbred population because the main interest is to locate genes that can be used for within-line selection. For a two generation experiment more animals had to be typed for marker loci to obtain a certain power than for a three generation experiment. Fewer trait values, however, had to be obtained for a two-generation experiment than for a three-generation experiment. A two or three-generation family structure with full-sib offspring was more efficient than a two or three-generation family structure with half-sib offspring. A family structure with full-sib grand-offspring, however, was less efficient than a family structure with half-sib grand-offspring. For the most efficient family structure each pair of parents had full-sib offspring that were genotyped for the marker. For the most-efficient family structure each full-sib offspring had half-sib grand-offspring for which trait values were obtained. For equal power with a heritability of 0.1 and 100 grand-offspring per full-sib offspring, 30-times less marker typings were required for this most efficient family structure than for a two-generation half-sib structure in which marker genotypes and trait values were obtained for half-sib offspring. The effect of heritability and the type of analysis (single marker or interval analysis) on the efficiency of a family structure is described. The results of this study should help to design QTL mapping experiments in an outbred population.     

Fine mapping and replication of QTL in outbred chicken advanced intercross lines

Background

Linkage mapping is used to identify genomic regions affecting the expression of complex traits. However, when experimental crosses such as F₂ populations or backcrosses are used to map regions containing a Quantitative Trait Locus (QTL), the size of the regions identified remains quite large, i.e. 10 or more Mb. Thus, other experimental strategies are needed to refine the QTL locations. Advanced Intercross Lines (AIL) are produced by repeated intercrossing of F₂ animals and successive generations, which decrease linkage disequilibrium in a controlled manner. Although this approach is seen as promising, both to replicate QTL analyses and fine-map QTL, only a few AIL datasets, all originating from inbred founders, have been reported in the literature.

Methods

We have produced a nine-generation AIL pedigree (n = 1529) from two outbred chicken lines divergently selected for body weight at eight weeks of age. All animals were weighed at eight weeks of age and genotyped for SNP located in nine genomic regions where significant or suggestive QTL had previously been detected in the F₂ population. In parallel, we have developed a novel strategy to analyse the data that uses both genotype and pedigree information of all AIL individuals to replicate the detection of and fine-map QTL affecting juvenile body weight.

Results

Five of the nine QTL detected with the original F₂ population were confirmed and fine-mapped with the AIL, while for the remaining four, only suggestive evidence of their existence was obtained. All original QTL were confirmed as a single locus, except for one, which split into two linked QTL.

Conclusions

Our results indicate that many of the QTL, which are genome-wide significant or suggestive in the analyses of large intercross populations, are true effects that can be replicated and fine-mapped using AIL. Key factors for success are the use of large populations and powerful statistical tools. Moreover, we believe that the statistical methods we have developed to efficiently study outbred AIL populations will increase the number of organisms for which in-depth complex traits can be analyzed.     

A haplotypic approach to founder-origin probabilities and outbred QTL analysis

Founder-origin probability methods are used to trace specific chromosomal segments in individual offspring. A haplotypic method was developed for calculating founder-origin probabilities in three-generation outbred pedigrees suited to quantitative trait locus (QTL) analysis. Estimators for expected founder-origin proportions were derived for a linkage group segment, an entire linkage group and a complete haplotype. If the founders are truly outbred, the haplotypic method gives a close approximation when compared with the Haley et al. (1994) method that simultaneously uses all marker information for QTL analysis, and it is less computationally demanding. The chief limitation of the haplotypic method is that some information in two-allele intercross marker-type configurations is ignored. Informativeness of marker arrays is discussed in the framework of founder-origin probabilities and proportions. The haplotypic method can be extended to more complex pedigrees with additional generations.     

Confirmation of crosses between lines of Agaricus brunnescens by isozyme analysis

In this paper are presented the results of isozyme analysis which confirmed intraspecific crosses between putative homokaryotic lines of Agaricus brunnescens. Putative homokaryotic lines were recognized by electrophoresis of single-spore-derived cultures and used as breeding stock. These breeding stock lines were grown together in dual culture on agar and selections were made from the interaction zone. These selections were then transferred to make spawn. Alternatively, spawns from each of two selected lines were mixed together and inoculated directly into compost. Intraspecific crosses were confirmed by the presence of heteromeric isozymes. Many of these newly developed lines were characterized by unique isozymic phenotypes reflecting unique genotypic classes.     

Power analysis of QTL detection in half-sib families using selective DNA pooling

Individual loci of economic importance (QTL) can be detected by comparing the inheritance of a trait and the inheritance of loci with alleles readily identifiable by laboratory methods (genetic markers). Data on allele segregation at the individual level are costly and alternatives have been proposed that make use of allele frequencies among progeny, rather than individual genotypes. Among the factors that may affect the power of the set up, the most important are those intrinsic to the QTL: the additive effect of the QTL, and its dominance, and distance between markers and QTL. Other factors are relative to the choice of animals and markers, such as the frequency of the QTL and marker alleles among dams and sires. Data collection may affect the detection power through the size of half-sib families, selection rate within families, and the technical error incurred when estimating genetic frequencies. We present results for a sensitivity analysis for QTL detection using pools of DNA from selected half-sibs. Simulations showed that conclusive detection may be achieved with families of at least 500 half-sibs if sires are chosen on the criteria that most of their marker alleles are either both missing, or one is fixed, among dams.     

QTL mapping under truncation selection in homozygous lines derived from biparental crosses

In plant breeding, a large number of progenies that will be discarded later in the breeding process must be phenotyped and marker genotyped for conducting QTL analysis. In many cases, phenotypic preselection of lines could be useful. However, in QTL analyses even moderate preselection can have a significant effect on the power of QTL detection and estimation of effects of the target traits. In this study, we provide exact formulas for quantifying the change of allele frequencies within marker classes, expectations of marker contrasts and the variance of the marker contrasts under truncation selection, for the general case of two QTL affecting the target trait and a correlated trait. We focused on homozygous lines derived at random from biparental crosses. The effects of linkage between the marker and the QTL under selection as well as the effect of selection on a correlated trait can be quantified with the given formulas. Theoretical results clearly show that depending on the magnitude of QTL effects, high selection intensities can lead to a dramatic reduction in power of QTL detection and that approximations based on the infinitesimal model deviate substantially from exact solutions. The presented formulas are valuable for choosing appropriate selection intensity when performing QTL mapping experiments on the data on phenotypically preselected traits and enable the calculation and bias correction of the effects of QTL under selection. Application of our theory to experimental data revealed that selection-induced bias of QTL effects can be successfully corrected.     

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulæ for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.     

QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses

Background

Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis.

Methodology/Principal Findings

In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits.

Conclusions/Significance

The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1–6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability.     

QTL analysis of body weight and conformation score in commercial broiler chickens using variance component and half-sib analyses

The aim of the study was to investigate quantitative trait loci (QTL) in previously identified regions of chicken chromosomes 1, 4 and 5 relating to 40-day body weights and conformation scores. Half-sib (HS) and variance component analyses were implemented and compared using QTL Express software. Data were from a two-generation design and consisted of 100 dam families nested in 46 sire families with trait values for 2,708 offspring. Chicken chromosome 4 showed nominal significance for QTL affecting body weight and conformation, and linkage was confirmed for both traits on chromosome 5. Results varied according to method of analysis and with common parent in the HS method.     

QTL mapping of yield-associated traits in Brassica juncea: meta-analysis and epistatic interactions using two different crosses between east European and Indian gene pool lines

Genetic analysis of 12 yield-associated traits was undertaken by dissection of quantitative trait loci (QTL) through meta-analysis and epistatic interaction studies in Brassica juncea. A consensus (integrated) map in B. juncea was constructed using two maps. These were VH map, developed earlier in the laboratory by using a DH population from the cross between Varuna and Heera (Pradhan et al. in Theor Appl Genet 106:607–614, 2003; Ramchiary et al. in Theor Appl Genet. 115:807–817, 2007; Panjabi et al. in BMC Genomics 9:113, 2008), and the TD map, developed in the present study using a DH population of 100 lines from the cross between TM-4 and Donskaja-IV. The TD map was constructed with 911 markers consisting of 585 AFLP, 8 SSR and 318 IP markers covering a total genome length of 1,629.9?cM. The consensus map constructed by using the common markers between the two maps contained a total of 2,662 markers and covered a total genome length of 1,927.1?cM. Firstly, QTL analysis of 12 yield-associated traits was undertaken for the TD population based on three-environment phenotypic data. Secondly, the three-environment phenotypic data for the same 12 quantitative traits generated by Ramchiary et al. (2007) were re-analyzed for the QTL detection in the VH map. Comparative analysis identified both common and population-specific QTL. The study revealed the presence of QTL clusters on LG A7, A8 and A10 in both TD and VH maps. Meta-analyses resolved 187 QTL distributed over nine linkage groups of TD and VH maps into 20 meta-QTL. Maximum resolution was recorded for the LG A10 wherein all the 54 QTL were mapped to a single meta-QTL within a confidence interval of 3.0?cM. Digenic epistatic interactions of QTL in both TD and VH maps revealed substantial additive?×?additive interactions showing a higher frequency of Type 1 and Type 2 interactions than Type 3 interactions. Some of the loci interacted with more than one locus indicating the presence of higher order epistatic interactions. These findings provided some detailed insight into the genetic architecture of the yield-associated traits in B. juncea.     

QTL mapping in outbred tetraploid (and diploid) diallel populations

Over the last decade, multiparental populations have become a mainstay of genetics research in diploid species. Our goal was to extend this paradigm to autotetraploids by developing software for quantitative trait locus (QTL) mapping in connected F1 populations derived from a set of shared parents. For QTL discovery, phenotypes are regressed on the dosage of parental haplotypes to estimate additive effects. Statistical properties of the model were explored by simulating half-diallel diploid and tetraploid populations with different population sizes and numbers of parents. Across scenarios, the number of progeny per parental haplotype (pph) largely determined the statistical power for QTL detection and accuracy of the estimated haplotype effects. Multiallelic QTL with heritability 0.2 were detected with 90% probability at 25 pph and genome-wide significance level 0.05, and the additive haplotype effects were estimated with over 90% accuracy. Following QTL discovery, the software enables a comparison of models with multiple QTL and nonadditive effects. To illustrate, we analyzed potato tuber shape in a half-diallel population with three tetraploid parents. A well-known QTL on chromosome 10 was detected, for which the inclusion of digenic dominance lowered the Deviance Information Criterion (DIC) by 17 points compared to the additive model. The final model also contained a minor QTL on chromosome 1, but higher-order dominance and epistatic effects were excluded based on the DIC. In terms of practical impacts, the software is already being used to select offspring based on the effect and dosage of particular haplotypes in breeding programs.     

Prediction of heterosis in crosses between inbred lines of Drosophila melanogaster

Summary The aim of the experiment was to determine if the estimated genetic distance between two populations could be used to predict the amount of heterosis that would occur when they were crossed. Eight lines of known relatedness to each other were produced by eight generations of sib mating and sub-lining. This produced lines that varied in coefficient of coancestry from zero to 0.78. Fourteen reciprocal crosses of these lines were used to measure heterosis for larval viability and adult fecundity. Gene frequencies at six polymorphic enzyme loci were used to estimate the genetic distances between lines, which were then compared with the known degrees of coancestry. The estimated genetic differences were poorly correlated with the known coancestry coefficients (r=0.4), possibly due to the small number of loci typed. Also genetic distances were only about 1/3 of what was expected. Selection acting on blocks of genes linked to the enzyme loci probably prevented the expected increase in homozygosity. Coancestry coefficient was correlated with heterosis (r=0.44–0.71). This level of correlation implied differences in heterosis among parent lines with the same level of coancestry. This variability is expected if a small number of loci explain most of the heterosis. The average level of heterosis was less than expected after eight generations of sib mating. This is most likely due to selection opposing the increase in homozygosity caused by inbreeding. The combination of these two imperfect correlations resulted in no significant correlation between genetic distance estimated from markers and heterosis.     

Selective genotyping for QTL detection using sib pair analysis in outbred populations with hierarchical structures

A simulation study illustrates the effects of the inclusion of half-sib pairs as well as the effects of selective genotyping on the power of detection and the parameter estimates in a sib pair analysis of data from an outbred population. The power of QTL detection obtained from samples of sib pairs selected according to their within family variance or according to the mean within family variance within half sib family was compared and contrasted with the power obtained when only full sib pair analysis was used. There was an increase in power (4–16%) and decrease in the bias of parameter estimates with the use of half-sib information. These improvements in power and parameter estimates depended on the number of the half sib pairs (half sib family size). Almost the same power as that obtained using all the available sib pairs could be achieved by selecting only 50–60% the animals. The most effective method was to select both full and half sib pairs on the basis of high within full sib family variance for the trait in question. The QTL position estimates were in general slightly biased towards the center of the chromosome and the QTL variance estimates were biased upwards, there being quite large differences in bias depending on the selection method.     

On the use of double haploids for detecting QTL in outbred populations

The power to detect quantitative trait loci (QTL) using the double haploid (DH), full-sib (FS) and hierarchical (HI) designs implemented in outbred fish populations was assessed for interval mapping using deterministic methods. The predictions were tested using simulation. The DH design was most efficient for the range of designs and parameters considered and was most beneficial when the FS design was not very powerful. The difference between the design was largest for a low amount of residual genetic variation. Accounting for an increase of the environmental variance due to the genetic constitution of the double haploid progeny changed the magnitude of the power, but the ranking of the designs remained the same. As large full sib family sizes can be obtained in fish, the practical value of HI designs as a strategy for increasing the power of QTL mapping experiments is limited when compared with the FS design. Overall, the results suggested that the DH design could be a very useful tool for QTL mapping in fish, and of particular importance when the effect of the QTL is low and the residual genetic variation from other chromosomes can be controlled by using multiple markers.