Quantitative trait locus analysis using recombinant inbred intercrosses: theoretical and empirical considerations

We describe a new approach, called recombinant inbred intercross (RIX) mapping, that extends the power of recombinant inbred (RI) lines to provide sensitive detection of quantitative trait loci (QTL) responsible for complex genetic and nongenetic interactions. RIXs are generated by producing F1 hybrids between all or a subset of parental RI lines. By dramatically extending the number of unique, reproducible genomes, RIXs share some of the best properties of both the parental RI and F2 mapping panels. These attributes make the RIX method ideally suited for experiments requiring analysis of multiple parameters, under different environmental conditions and/or temporal sampling. However, since any pair of RIX genomes shares either one or no parental RIs, this cross introduces an unusual population structure requiring special computational approaches for analysis. Herein, we propose an efficient statistical procedure for QTL mapping with RIXs and describe a novel empirical permutation procedure to assess genome-wide significance. This procedure will also be applicable to diallel crosses. Extensive simulations using strain distribution patterns from CXB, AXB/BXA, and BXD mouse RI lines show the theoretical power of the RIX approach and the analysis of CXB RIXs demonstrates the limitations of this procedure when using small RI panels.     

Mapping multiple QTL of different effects: comparison of a simple sequential testing strategy and multiple QTL mapping

The aim of this study was to explore, by computer simulation, the mapping of QTLs in a realistic but complex situation of many (linked) QTLs with different effects, and to compare two QTL mapping methods. A novel method to dissect genetic variation on multiple chromosomes using molecular markers in backcross and F₂ populations derived from inbred lines was suggested, and its properties tested using simulations. The rationale for this sequential testing method was to explicitly test for alternative genetic models. The method consists of a series of four basic statistical tests to decide whether variance was due to a single QTL, two QTLs, multiple QTLs, or polygenes, starting with a test to detect genetic variance associated with a particular chromosome. The method was able to distinguish between different QTL configurations, in that the probability to `detect' the correct model was high, varying from 0.75 to 1. For example, for a backcross population of 200 and an overall heritability of 50%, in 78% of replicates a polygenic model was detected when that was the underlying true model. To test the method for multiple chromosomes, QTLs were simulated on 10 chromosomes, following a geometric series of allele effects, assuming positive alleles were in coupling in the founder lines For these simulations, the sequential testing method was compared to the established Multiple QTL Mapping (MQM) method. For a backcross population of 400 individuals, power to detect genetic variance was low with both methods when the heritability was 0.40. For example, the power to detect genetic variation on a chromosome on which 6 QTLs explained 12.6% of the genetic variance, was less than 60% for both methods. For a large heritability (0.90), the power of MQM to detect genetic variance and to dissect QTL configurations was generally better, due to the simultaneous fitting of markers on all chromosomes. It is concluded that when testing different QTL configurations on a single chromosome using the sequential testing procedure, regions of other chromosomes which explain a significant amount of variation should be fitted in the model of analysis. This study reinforces the need for large experiments in plants and other species if the aim of a genome scan is to dissect quantitative genetic variation.     

Mapping and Isolation of Quantitative Trait Loci Controlling Plant Height and Heading Date in Rice

Quantitative trait loci (QTL) were identified for heading date and plant height in rice ( Oryza sativa L.) using a recombinant inbred line population consisting of 241 lines. Totally 4 QTLs for heading date and 4 QTLs for plant height were detected in three years. The QTL with large effects located in the interval C1023-R1440 on chromosome 7 was simultaneously detected in three years for both traits. In order to distinguished the interval whether contained one QTL with pleiotropy effect or two close linked QTLs, a recombinant line RIL50, whose genetic background was high similar to Zhenshan 97 except the regions covered the major QTL from Minghui 63, was selected to cross with Zhenshan 97. A BC1F2 population from the cross, which could be regarded as near isogenic lines (NIL) with the targeted QTL (QTL-NIL), was used to collect heading date and plant height data. The frequency distribution of the two traits in the BC1F2 population was bimodal, and their segregation ratios were in accordance with the expected Mendelian inheritance ratios. Normally, the short plants flowered early in the population, the high plants with late heading date, but the relationships between the plant height and the heading date of 6 plants conflicted with the case. The above results clearly demonstrated that QTL could be treated as single Mendelian factor. Moreover, there are two close linked genes controlling the heading date and the plant height on chromosome 7, respectively.     

Development of a near-isogenic line population of Arabidopsis thaliana and comparison of mapping power with a recombinant inbred line population

In Arabidopsis recombinant inbred line (RIL) populations are widely used for quantitative trait locus (QTL) analyses. However, mapping analyses with this type of population can be limited because of the masking effects of major QTL and epistatic interactions of multiple QTL. An alternative type of immortal experimental population commonly used in plant species are sets of introgression lines. Here we introduce the development of a genomewide coverage near-isogenic line (NIL) population of Arabidopsis thaliana, by introgressing genomic regions from the Cape Verde Islands (Cvi) accession into the Landsberg erecta (Ler) genetic background. We have empirically compared the QTL mapping power of this new population with an already existing RIL population derived from the same parents. For that, we analyzed and mapped QTL affecting six developmental traits with different heritability. Overall, in the NIL population smaller-effect QTL than in the RIL population could be detected although the localization resolution was lower. Furthermore, we estimated the effect of population size and of the number of replicates on the detection power of QTL affecting the developmental traits. In general, population size is more important than the number of replicates to increase the mapping power of RILs, whereas for NILs several replicates are absolutely required. These analyses are expected to facilitate experimental design for QTL mapping using these two common types of segregating populations.     

The genetic contribution to heart rate and heart rate variability in quiescent mice

Recent studies have suggested a genetic component to heart rate (HR) and HR variability (HRV). However, a systematic examination of the genetic contribution to the variation in HR and HRV has not been performed. This study investigated the genetic contribution to HR and HRV using a wide range of inbred and recombinant inbred (RI) mouse strains. Electrocardiogram data were recorded from 30 strains of inbred mice and 29 RI strains. Significant differences in mean HR and total power (TP) HRV were identified between inbred strains and RI strains. Multiple significant differences within the strain sets in mean low-frequency (LF) and high-frequency (HF) power were also found. No statistically significant concordance was found between strain distribution patterns for HR and HRV phenotypes. Genomewide interval mapping identified a significant quantitative trait locus (QTL) for HR [LOD (likelihood of the odds) score = 3.763] on chromosome 6 [peak at 53.69 megabases (Mb); designated HR 1 (Hr1)]. Suggestive QTLs for TP were found on chromosomes 2, 4, 5, 6, and 14. A suggestive QTL for LF was found on chromosome 16; for HF, we found one significant QTL on chromosome 5 (LOD score = 3.107) [peak at 53.56 Mb; designated HRV-high-frequency 1 (Hrvhf1)] and three suggestive QTLs on chromosomes 2, 11 and 15. In conclusion, the results demonstrate a strong genetic component in the regulation of resting HR and HRV evidenced by the significant differences between strains. A lack of correlation between HR and HRV phenotypes in some inbred strains suggests that different sets of genes control the phenotypes. Furthermore, QTLs were found that will provide important insight to the genetic regulation of HR and HRV at rest.     

Quantitative trait mapping in a diallel cross of recombinant inbred lines

A recombinant inbred intercross (RIX) is created by generating diallel F₁ progeny from one or more panels of recombinant inbred (RI) strains. This design was originally introduced to extend the power of small RI panels for the confirmation of quantitative trait loci (QTL) provisionally detected in a parental RI set. For example, the set of 13 C × B (C57BL/6ByJ × BALB/cByJ) RI strains can, in principle, be supplemented with 156 isogenic F₁s. We describe and test a method of analysis, based on a linear mixed model, that accounts for the correlation structure of RIX populations. This model suggests a novel permutation algorithm that is needed to obtain appropriate threshold values for genome-wide scans of an RIX population. Despite the combinational multiplication of unique genotypes that can be generated using an RIX design, the effective sample size of the RIX population is limited by the number of progenitor RI genomes that are combined. When using small RI panels such as the C × B there appears to be only modest advantage of the RIX design when compared with the original RI panel for detecting QTLs with additive effects. The RIX, however, does have an inherent ability to detect dominance effects, and, unlike RI strains, the RIX progeny are genetically reproducible but are not fully inbred, providing somewhat more natural genetic context. We suggest a breeding strategy, the balanced partial RIX, that balances the advantage of RI and RIX designs. This involves the use of a partial RIX population derived from a large RI panel in which the available information is maximized by minimizing correlations among RIX progeny.     

Power analysis for quantitative trait locus mapping in populations derived by multiple backcrosses

 Populations derived by multiple backcrosses are potentially useful for quantitative trait locus (QTL) mapping studies. Comparisons of relative power to detect QTL using populations derived by multiple back-crosses are needed to make decisions when mapping projects are initiated. The objective of this study was to theoretically compare the power to detect QTL in populations derived by multiple backcrosses relative to mapping in a recombinant inbred population of equal size. Backcrossing results in a reduction in genetic variance with each generation and also results in an increasing frequency of the recurrent parent marker genotype. The relevant outcome for QTL mapping is a reduction in genetic variance to partition between marker genotype classes and increasing unbalance of the number of individuals contributing to the mean of the marker genotypes. Both of these factors lead to a decrease in the power to detect a QTL as the number of backcross generations increases. Experimental error was held constant with the populations compared. From a theoretical standpoint, backcross-derived populations offer few advantages for QTL detection. If, however, a backcrossing approach is the most efficient method to achieve a desired breeding objective and if QTL detection is an objective of equal or less importance, backcross-derived populations are a reasonable approach to QTL detection. Received: 4 August 1996 / Accepted: 4 April 1997     

Mapping epistatic quantitative trait loci with one-dimensional genome searches

The discovery of epistatically interacting QTL is hampered by the intractability and low power to detect QTL in multidimensional genome searches. We describe a new method that maps epistatic QTL by identifying loci of high QTL by genetic background interaction. This approach allows detection of QTL involved not only in pairwise but also higher-order interaction, and does so with one-dimensional genome searches. The approach requires large populations derived from multiple related inbred-line crosses as is more typically available for plants. Using maximum likelihood, the method contrasts models in which QTL allelic values are either nested within, or fixed over, populations. We apply the method to simulated doubled-haploid populations derived from a diallel among three inbred parents and illustrate the power of the method to detect QTL of different effect size and different levels of QTL by genetic background interaction. Further, we show how the method can be used in conjunction with standard two-locus QTL detection models that use two-dimensional genome searches and find that the method may double the power to detect first-order epistasis.     

Quantitative trait loci controlling aluminium tolerance in two accessions of Arabidopsis thaliana (Landsberg erecta and Cape Verde Islands)

Quantitative trait loci (QTL) analysis of aluminium (Al) tolerance was performed using Ler/Cvi recombinant inbred (RI) lines of Arabidopsis thaliana. Relative root length (RRL) (root length with 4 µm Al/root length with no Al at pH 5.0) on day 5 was used as the Al tolerance index for QTL analysis. Al tolerance judged by RRL was well correlated to tolerance judged by other indexes, including accumulation of callose, reactive oxygen species in the root apex and growth performance on acid soil containing a large amount of exchangeable Al. Using data sets with an h_b² of 0.91, two QTLs were detected at the top of chromosome 1 and bottom of chromosome 3. These QTLs explained 40 and 16% of the phenotypic variation of Al tolerance, respectively, and the positive effect of the Cvi allele. The QTL on chromosome 1 overlapped with a major QTL in another recombinant inbred population, and is possibly related to malate excretion. A complete pair-wise search revealed 11 sets of epistatic interacting loci pairs, which accounted for the transgressive segregation among the RI population. Several epistatic interactions shared the same chromosomal region, indicating the possible involvement of regulatory proteins in Al tolerance in Arabidopsis.     

Varying coefficient models for mapping quantitative trait loci using recombinant inbred intercrosses

There has been a great deal of interest in the development of methodologies to map quantitative trait loci (QTL) using experimental crosses in the last 2 decades. Experimental crosses in animal and plant sciences provide important data sources for mapping QTL through linkage analysis. The Collaborative Cross (CC) is a renewable mouse resource that is generated from eight genetically diverse founder strains to mimic the genetic diversity in humans. The recombinant inbred intercrosses (RIX) generated from CC recombinant inbred (RI) lines share similar genetic structures of F(2) individuals but with up to eight alleles segregating at any one locus. In contrast to F(2) mice, genotypes of RIX can be inferred from the genotypes of their RI parents and can be produced repeatedly. Also, RIX mice typically do not share the same degree of relatedness. This unbalanced genetic relatedness requires careful statistical modeling to avoid false-positive findings. Many quantitative traits are inherently complex with genetic effects varying with other covariates, such as age. For such complex traits, if phenotype data can be collected over a wide range of ages across study subjects, their dynamic genetic patterns can be investigated. Parametric functions, such as sigmoidal or logistic functions, have been used for such purpose. In this article, we propose a flexible nonparametric time-varying coefficient QTL mapping method for RIX data. Our method allows the QTL effects to evolve with time and naturally extends classical parametric QTL mapping methods. We model the varying genetic effects nonparametrically with the B-spline bases. Our model investigates gene-by-time interactions for RIX data in a very flexible nonparametric fashion. Simulation results indicate that the varying coefficient QTL mapping has higher power and mapping precision compared to parametric models when the assumption of constant genetic effects fails. We also apply a modified permutation procedure to control overall significance level.     

Recombinant near-isogenic lines: a resource for the mendelization of heterotic QTL in maize

Although heterosis is widely exploited in agriculture, a clear understanding of its genetic bases is still elusive. This work describes the development of maize recombinant near-isogenic lines (NILs) for the mendelization of six heterotic QTL previously identified based on a maize (Zea mays L.) RIL population. The efficient and inexpensive strategy adopted to generate sets of NILs starting from QTL-specific residual heterozygous lines (RHLs) is described and validated. In particular, we produced nine pairs of recombinant NILs for all six QTL starting from RHLs F_4:5 originally obtained during the production of the RIL population mentioned above. Whenever possible, two different NIL pairs were generated for each QTL. The efficiency of this procedure was tested by analyzing two segregating populations for two of the selected heterotic QTL for plant height, yield per plant and ears per plant. Both additive and dominant effects were observed, consistently with the presence of the QTL within the introgressed regions. Refinement of QTL detection was consistent with previous observations in terms of effects and position of the considered QTL. The genetic material developed in this work represents the starting point for QTL fine mapping aimed at understanding the genetic bases of hybrid vigor in maize. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The Power of QTL Mapping with RILs

QTL (quantitative trait loci) mapping is commonly used to identify genetic regions responsible to important phenotype variation. A common strategy of QTL mapping is to use recombinant inbred lines (RILs), which are usually established by several generations of inbreeding of an F1 population (usually up to F6 or F7 populations). As this inbreeding process involves a large amount of labor, we are particularly interested in the effect of the number of inbreeding generations on the power of QTL mapping; a part of the labor could be saved if a smaller number of inbreeding provides sufficient power. By using simulations, we investigated the performance of QTL mapping with recombinant inbred lines (RILs). As expected, we found that the power of F4 population could be almost comparable to that of F6 and F7 populations. A potential problem in using F4 population is that a large proportion of RILs are heterozygotes. We here introduced a new method to partly relax this problem. The performance of this method was verified by simulations with a wide range of parameters including the size of the segregation population, recombination rate, genome size and the density of markers. We found our method works better than the commonly used standard method especially when there are a number of heterozygous markers. Our results imply that in most cases, QTL mapping does not necessarily require RILs at F6 or F7 generations; rather, F4 (or even F3) populations would be almost as useful as F6 or F7 populations. Because the cost to establish a number of RILs for many generations is enormous, this finding will cause a reduction in the cost of QTL mapping, thereby accelerating gene mapping in many species.     

Fine Mapping QTL for Drought Resistance Traits in Rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) Using Bulk Segregant Analysis

Drought stress is a major limitation to rice (Oryza sativa L.) yields and its stability, especially in rainfed conditions. Developing rice cultivars with inherent capacity to withstand drought stress would improve rainfed rice production. Mapping quantitative trait loci (QTLs) linked to drought resistance traits will help to develop rice cultivars suitable for water-limited environments through molecular marker-assisted selection (MAS) strategy. However, QTL mapping is usually carried out by genotyping large number of progenies, which is labour-intensive, time-consuming and cost-ineffective. Bulk segregant analysis (BSA) serves as an affordable strategy for mapping large effect QTLs by genotyping only the extreme phenotypes instead of the entire mapping population. We have previously mapped a QTL linked to leaf rolling and leaf drying in recombinant inbred (RI) lines derived from two locally adapted indica rice ecotypes viz., IR20/Nootripathu using BSA. Fine mapping the QTL will facilitate its application in MAS. BSA was done by bulking DNA of 10 drought-resistant and 12 drought-sensitive RI lines. Out of 343 rice microsatellites markers genotyped, RM8085 co-segregated among the RI lines constituting the respective bulks. RM8085 was mapped in the middle of the QTL region on chromosome 1 previously identified in these RI lines thus reducing the QTL interval from 7.9 to 3.8 cM. Further, the study showed that the region, RM212–RM302–RM8085–RM3825 on chromosome 1, harbours large effect QTLs for drought-resistance traits across several genetic backgrounds in rice. Thus, the QTL may be useful for drought resistance improvement in rice through MAS and map-based cloning.     

Detection of quantitative trait Loci influencing recombination using recombinant inbred lines

The genetic basis of variation in recombination in higher plants is polygenic and poorly understood, despite its theoretical and practical importance. Here a method of detecting quantitative trait loci (QTL) influencing recombination in recombinant inbred lines (RILs) is proposed that relies upon the fact that genotype data within RILs carry the signature of past recombination. Behavior of the segregational genetic variance in numbers of chromosomal crossovers (recombination) over generations is described for self-, full-sib-, and half-sib-generated RILs with no dominance in true crossovers. This genetic variance, which as a fraction of the total phenotypic variance contributes to the statistical power of the method, was asymptotically greatest with half sibbing, less with sibbing, and least with selfing. The statistical power to detect a recombination QTL declined with diminishing QTL effect, genome target size, and marker density. For reasonably tight marker linkage power was greater with less intense inbreeding for later generations and vice versa for early generations. Generational optima for segregation variance and statistical power were found, whose onset and narrowness varied with marker density and mating design, being more pronounced for looser marker linkage. Application of this method to a maize RIL population derived from inbred lines Mo17 and B73 and developed by selfing suggested two putative QTL (LOD > 2.4) affecting certain chromosomes, and using a canonical transformation another putative QTL was detected. However, permutation tests failed to support their presence (experimentwise alpha = 0.05). Other populations with more statistical power and chosen specifically for recombination QTL segregation would be more effective.     

Genetic mapping of the gene affecting polyphenol oxidase activity in tetraploid durum wheat

The quality of durum wheat (Triticum turgidum ssp. durum) is influenced by polyphenol oxidase(PPO) activity and its corresponding substrates. A saturated molecular-marker linkage map was constructed previously by using a set of recombinant inbred (RI) lines, derived from a cross between durum wheat cultivars Jennah Khetifa and Cham 1. Quantitative trait loci (QTL) for PPO activity in seeds were mapped in this population. PPO activity in seeds of the parents and 110 RI lines was measured spectrophotometrically. The PPO activity of Cham 1 was significantly lower than that of Jennah Khetifa. QTL analysis of these data indicated that most of PPO activity was associated with major loci on the long arm of chromosome 2A. The trait was found to be strongly associated with the SSR marker Xgwm312@2A. With this knowledge, marker-assisted selection can be used to select genotypes with lower PPO activity in durum wheat populations.     

应用二种定位法比较不同世代水稻产量性状QTL的检测结果

应用珍汕97B／密阳46的F2和重组自交系（RIL）群体,建立RFLP连锁图,检测控制稻谷产量及其5个构成因子的QTL。结果表明,具有较大加性效应者,能同时在F2和RIL群体中检测到。而且,在重组自交系群体中,发现设重复的表型鉴定与基于单株的表型鉴定,对效应较高的QTL的检测影响不大。     

Environment-dependent survival of Drosophila melanogaster: a quantitative genetic analysis

Summary Survival under starvation conditions was investigated in relationship to survival when food was present because these traits could be linked by evolutionary history. Recombinant inbred lines derived from natural populations of Drosophila melanogaster were used to test genetic correlations and architecture of these survival traits. Sexes were genetically correlated within traits and there was significant correlation between survival traits. A number of quantitative trait loci (QTLs) were present for starvation survival and/or survival on food. In general, the QTL effects were consistent for sexes and environments. QTL effects were found on each major chromosome, but the major effects were largely localized on the second chromosome. Importantly, the 'four-allele' progenitor of the recombinant inbred lines used in the present study allowed the sign and magnitude of effects to be assigned to linkage groups. One such linkage group on the second chromosome conferred starvation resistance and longevity, supporting the hypothesis of an association between starvation resistance and lifespan.     

Quantitative trait loci (QTL) detection in multicross inbred designs: recovering QTL identical-by-descent status information from marker data

Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two inbred lines. The power of such QTL detection and the parameter estimates depend largely on the choice of the two parental lines. Thus, the QTL detected in such populations represent only a small part of the genetic architecture of the trait. In addition, the effects of only two alleles are characterized, which is of limited interest to the breeder, while common pedigree breeding material remains unexploited for QTL mapping. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population obtained from inbred parents. We then investigate with simulated data mimicking conventional breeding programs the influence of different estimates of the IBD values on the power of QTL detection. The proposed method would provide an alternative to the development of specifically designed recombinant populations, by utilizing the genetic variation actually managed by plant breeders. The use of these detected QTL in assisting breeding would thus be facilitated.     

Joint linkage QTL analyses for partial resistance to Phytophthora sojae in soybean using six nested inbred populations with heterogeneous conditions

Partial resistance to Phytophthora sojae in soybean is controlled by multiple quantitative trait loci (QTL). With traditional QTL mapping approaches, power to detect such QTL, frequently of small effect, can be limited by population size. Joint linkage QTL analysis of nested recombinant inbred line (RIL) populations provides improved power to detect QTL through increased population size, recombination, and allelic diversity. However, uniform development and phenotyping of multiple RIL populations can prove difficult. In this study, the effectiveness of joint linkage QTL analysis was evaluated on combinations of two to six nested RIL populations differing in inbreeding generation, phenotypic assay method, and/or marker set used in genotyping. In comparison to linkage analysis in a single population, identification of QTL by joint linkage analysis was only minimally affected by different phenotypic methods used among populations once phenotypic data were standardized. In contrast, genotyping of populations with only partially overlapping sets of markers had a marked negative effect on QTL detection by joint linkage analysis. In total, 16 genetic regions with QTL for partial resistance against P. sojae were identified, including four novel QTL on chromosomes 4, 9, 12, and 16, as well as significant genotype-by-isolate interactions. Resistance alleles from PI 427106 or PI 427105B contributed to a major QTL on chromosome 18, explaining 10–45 % of the phenotypic variance. This case study provides guidance on the application of joint linkage QTL analysis of data collected from populations with heterogeneous assay conditions and a genetic framework for partial resistance to P. sojae.