Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice

This study was conducted to determine whether quantitative trait loci (QTL) controlling traits of agronomic importance detected in recombinant inbred lines (RILs) are also expressed in testcross (TC) hybrids of rice. A genetic map was constructed using an RIL population derived from a cross between B5 and Minghui 63, a parent of the most widely grown hybrid rice cultivar in China. Four TC hybrid populations were produced by crossing the RILs with three maintaining lines for the widely used cytoplasmic male-sterile (CMS) lines and the genic male-sterile line Peiai64s. The mean values of the RILs for the seven traits investigated were significantly correlated to those of the F1 hybrids in the four TC populations. Twenty-seven main-effect QTL were identified in the RILs. Of these, the QTL that had the strongest effect on each of the seven traits in the RILs was detected in two or more of the TC populations, and six other QTL were detected in one TC population. Epistatic analysis revealed that the effect of epistatic QTL was relatively weak and cross combination specific. Searching publicly available QTL data in rice revealed the positional convergence of the QTL with the strongest effect in a wide range of populations and under different environments. Since the main-effect QTL is expressed across different testers, and in different genetic backgrounds and environments, it is a valuable target for gene manipulation and for further application in rice breeding. When a restorer line that expresses main-effect QTL is bred, it could be used in a number of cross combinations.     

Bayesian multiple quantitative trait loci mapping for recombinant inbred intercrosses

The Collaborative Cross (CC) is a renewable mouse resource that mimics the genetic diversity in humans. The recombinant inbred intercrosses (RIX) generated from CC recombinant inbred (RI) lines share similar genetic structures to those of F(2) individuals. 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 do not typically share the same degree of relatedness. This unbalanced genetic relatedness requires careful statistical modeling to avoid a large number of false positive findings. For complex traits, mapping multiple genes simultaneously is arguably more powerful than mapping one gene at a time. In this article, we describe how we have developed a Bayesian quantitative trait locus (QTL) mapping method that simultaneously deals with the special genetic architecture of RIX and maps multiple genes. The performance of the proposed method is evaluated by extensive simulations. In addition, for a given set of RI lines, there are numerous ways to generate RIX samples. To provide a general guideline on future RIX studies, we compare several RIX designs through simulations.     

Genetic expectations of quantitative trait loci main and interaction effects obtained with the triple testcross design and their relevance for the analysis of heterosis

Interpretation of experimental results from quantitative trait loci (QTL) mapping studies on the predominant type of gene action can be severely affected by the choice of statistical model, experimental design, and provision of epistasis. In this study, we derive quantitative genetic expectations of (i) QTL effects obtained from one-dimensional genome scans with the triple testcross (TTC) design and (ii) pairwise interactions between marker loci using two-way analyses of variance (ANOVA) under the F(2)- and the F(infinity)-metric model. The theoretical results show that genetic expectations of QTL effects estimated with the TTC design are complex, comprising both main and epistatic effects, and that genetic expectations of two-way marker interactions are not straightforward extensions of effects estimated in one-dimensional scans. We also demonstrate that the TTC design can partially overcome the limitations of the design III in separating QTL main effects and their epistatic interactions in the analysis of heterosis and that dominance x additive epistatic interactions of individual QTL with the genetic background can be estimated with a one-dimensional genome scan. Furthermore, we present genetic expectations of variance components for the analysis of TTC progeny tested in a split-plot design, assuming digenic epistasis and arbitrary linkage.     

Quantitative trait loci for rice yield-related traits using recombinant inbred lines derived from two diverse cultivars

The thousand-grain weight and spikelets per panicle directly contribute to rice yield. Heading date and plant height also greatly influence the yield. Dissection of genetic bases of yield-related traits would provide tools for yield improvement. In this study, quantitative trait loci (QTL) mapping for spikelets per panicle, thousand-grain weight, heading date and plant height was performed using recombinant inbred lines derived from a cross between two diverse cultivars, Nanyangzhan and Chuan7. In total, 20 QTLs were identified for four traits. They were located to 11 chromosomes except on chromosome 4. Seven and five QTLs were detected for thousand-grain weight and spikelets per panicle, respectively. Four QTLs were identified for both heading date and plant height. About half the QTLs were commonly detected in both years, 2006 and 2007. Six QTLs are being reported for the first time. Two QTL clusters were identified in regions flanked by RM22065 and RM5720 on chromosome 7 and by RM502 and RM264 on chromosome 8, respectively. The parent, Nanyangzhan with heavy thousand-grain weight, carried alleles with increased effects on all seven thousand-grain weight QTL, which explained why there was no transgressive segregation for thousand-grain weight in the population. In contrast, Chuan7 with more spikelets per panicle carried positive alleles at all five spikelets per panicle QTL except qspp5. Further work on distinction between pleiotropic QTL and linked QTL is needed in two yield-related QTL clusters.     

Serum adiponectin concentration: its correlation with diabetes-related traits and quantitative trait loci analysis in mouse SMXA recombinant inbred strains

Adiponectin is thought to be an important mediator of insulin sensitivity and atherosclerosis. Using mouse 19 SMXA recombinant inbred (RI) strains, a powerful tool for analyzing multifactorial genetic traits, we found relationships between serum adiponectin levels and diabetes-related traits, body mass index, and serum lipid levels, and also determined the loci controlling serum adiponectin levels by quantitative trait loci (QTL) analysis. RI strains exhibited widely ranging serum adiponectin concentration distribution patterns and diabetes-related traits. The serum adiponectin concentration showed the strongest negative correlation with fasting serum insulin concentration, but negative correlations were also observed with serum triglycerides, cholesterol, and liver weight. In contrast, neither the body mass index nor the blood glucose concentration correlated with serum adiponectin levels. These results suggest that hypoadiponectinemia might be used as a predictor of insulin resistance. In addition, two suggestive QTLs for serum adiponectin concentration were detected on Chromosome (Chr) 7, and an A/J allele at these loci was associated with elevated serum adiponectin concentrations. Identification of genes responsible for regulating the serum adiponectin concentration might lead to the development of novel treatments for patients with diabetes concomitant with hypoadiponectinemia.     

Quantitative trait locus analysis of growth-related traits in a new Arabidopsis recombinant inbred population

Arabidopsis natural variation was used to analyze the genetics of plant growth rate. Screening of 22 accessions revealed a large variation for seed weight, plant dry weight and relative growth rate but not for water content. A positive correlation was observed between seed weight and plant area 10 d after planting, suggesting that seed weight affects plant growth during early phases of development. During later stages of plant growth this correlation was not significant, indicating that other factors determine growth rate during this phase. Quantitative trait locus (QTL) analysis, using 114 (F9 generation) recombinant inbred lines derived from the cross between Landsberg erecta (Ler, from Poland) and Shakdara (Sha, from Tadjikistan), revealed QTLs for seed weight, plant area, dry weight, relative growth rate, chlorophyll fluorescence, flowering time, and flowering-related traits. Growth traits (plant area, dry weight, and relative growth rate) colocated at five genomic regions. At the bottom of chromosome 5, colocation was found of QTLs for leaf area, leaf initiation speed, specific leaf area, and chlorophyll fluorescence but not for dry weight, indicating that this locus might be involved in leaf development. No consistent relation between growth traits and flowering time was observed despite some colocations. Some of the QTLs detected for flowering time overlapped with loci detected in other recombinant inbred line populations, but also new loci were identified. This study shows that Arabidopsis can successfully be used to study the genetic basis of complex traits like plant growth rate.     

Using crossover breakpoints in recombinant inbred lines to identify quantitative trait loci controlling the global recombination frequency

Recombination is a crucial component of evolution and breeding, producing new genetic combinations on which selection can act. Rates of recombination vary tremendously, not only between species but also within species and for specific chromosomal segments. In this study, by examining recombination events captured in recombinant inbred mapping populations previously created for maize, wheat, Arabidopsis, and mouse, we demonstrate that substantial variation exists for genomewide crossover rates in both outcrossed and inbred plant and animal species. We also identify quantitative trait loci (QTL) that control this variation. The method that we developed and employed here holds promise for elucidating factors that regulate meiotic recombination and for creation of hyperrecombinogenic lines, which can help overcome limited recombination that hampers breeding progress.     

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.     

Mapping 49 quantitative trait loci at high resolution through sequencing-based genotyping of rice recombinant inbred lines

Mapping chromosome regions responsible for quantitative phenotypic variation in recombinant populations provides an effective means to characterize the genetic basis of complex traits. We conducted a quantitative trait loci (QTL) analysis of 150 rice recombinant inbred lines (RILs) derived from a cross between two cultivars, Oryza sativa ssp. indica cv. 93-11 and Oryza sativa ssp. japonica cv. Nipponbare. The RILs were genotyped through next-generation sequencing, which accurately determined the recombination breakpoints and provided a new type of genetic markers, recombination bins, for QTL analysis. We detected 49 QTL with phenotypic effect ranging from 3.2 to 46.0% for 14 agronomics traits. Five QTL of relatively large effect (14.6–46.0%) were located on small genomic regions, where strong candidate genes were found. The analysis using sequencing-based genotyping thus offers a powerful solution to map QTL with high resolution. Moreover, the RILs developed in this study serve as an excellent system for mapping and studying genetic basis of agricultural and biological traits of rice.     

Mapping quantitative trait loci using the experimental designs of recombinant inbred populations

In the data collection of the QTL experiments using recombinant inbred (RI) populations, when individuals are genotyped for markers in a population, the trait values (phenotypes) can be obtained from the genotyped individuals (from the same population) or from some progeny of the genotyped individuals (from the different populations). Let Fu be the genotyped population and Fv (v>or=u) be the phenotyped population. The experimental designs that both marker genotypes and phenotypes are recorded on the same populations can be denoted as (Fu/Fv, u=v) designs and that genotypes and phenotypes are obtained from the different populations can be denoted as (Fu/Fv, v>u) designs. Although most of the QTL mapping experiments have been conducted on the backcross and F2(F2/F2) designs, the other (Fu/Fv, v>or=u) designs are also very popular. The great benefits of using the other (Fu/Fv, v>or=u) designs in QTL mapping include reducing cost and environmental variance by phenotyping several progeny for the genotyped individuals and taking advantages of the changes in population structures of other RI populations. Current QTL mapping methods including those for the (Fu/Fv, u=v) designs, mostly for the backcross or F2/F2 design, and for the F2/F3 design based on a one-QTL model are inadequate for the investigation of the mapping properties in the (Fu/Fv, uor=u) designs. In addition, the QTL mapping properties of the proposed and approximate methods in different designs are discussed. Simulations were performed to evaluate the performance of the proposed and approximate methods. The proposed method is proven to be able to correct the problems of the approximate and current methods for improving the resolution of genetic architecture of quantitative traits and can serve as an effective tool to explore the QTL mapping study in the system of RI populations.     

New Arabidopsis recombinant inbred line populations genotyped using SNPWave and their use for mapping flowering-time quantitative trait loci

The SNPWave marker system, based on SNPs between the reference accessions Colombia-0 and Landsberg erecta (Ler), was used to distinguish a set of 92 Arabidopsis accessions from various parts of the world. In addition, we used these markers to genotype three new recombinant inbred line populations for Arabidopsis, having Ler as a common parent that was crossed with the accessions Antwerp-1, Kashmir-2, and Kondara. The benefit of using multiple populations that contain many similar markers and the fact that all markers are linked to the physical map of Arabidopsis facilitates the quantitative comparison of maps. Flowering-time variation was analyzed in the three recombinant inbred line populations. Per population, four to eight quantitative trait loci (QTL) were detected. The comparison of the QTL positions related to the physical map allowed the estimate of 12 different QTL segregating for flowering time for which Ler has an allele different from one, two, or three of the other accessions.     

Genetic resolution and verification of quantitative trait loci for flowering and plant height with recombinant inbred lines of maize.

Recombinant inbred (RI) lines offer several advantages for detecting quantitative trait loci (QTLs), including increased precision of trait measurements, power for detection of additive effects, and resolution of linked QTLs. This study was conducted to detect and characterize QTLs in maize for flowering and plant height and to compare QTL detection in an early (F2:3) generation of the same population. One hundred and eighty-six RIs from a cross between inbred lines Mo17 and H99 were evaluated in a replicated field experiment and analyzed at 101 loci detected by restriction fragment length polymorphisms. QTLs were identified by single-factor analysis of variance. A total of 59 QTLs were detected for plant height, ear height, top height, anthesis, silk emergence, and anthesis to silk interval. Individual QTLs explained 2.2-15.4% of trait variation, and multiple models including all QTLs detected for a trait explained up to 52.5% of the phenotypic variation. Comparison of QTLs detected with 150 F2:3 lines from the same population indicated that 16 (70%) of the 23 F2:3 QTLs were also observed in the F6:7 generation. Parental effects were consistent across generations. At 14 of the 16 QTLs detected in both generations, genetic effects were smaller in the F6:7. Also, some QTLs detected in the F2:3 were resolved into multiple linked QTLs in the F6:7, indicating the additional power of RI populations for mapping, with important implications for marker-assisted selection as well as map-based cloning of QTLs. Key words : Zea mays, RFLP, plant breeding, genetics, recombination.     

Comparison of quantitative trait loci controlling seedling characteristics at two seedling stages using rice recombinant inbred lines

A better understanding of the genetics of seedling characteristics in rice could be helpful in improving rice varieties. Zhenshan 97 and Minghui 63, the parents of Shanyou 63, an elite hybrid developed during the last decade in China, vary greatly with respect to their physiological and morphological traits at the seedling growth stage. In this study, we used a population of 240 recombinant inbred lines derived from a cross between Zhenshan 97 and Minghui 63 to identify quantitative trait loci (QTL) for seedling characteristics. All plant material was grown in hydroponic culture. Data for the following characters were collected at 30 days and 40 days post-sowing: plant height, shoot dry matter weight (SDW), maximum root length, root dry weight (RDW), total dry weight , and root-shoot ratio (the ratio of SDW to RDW). Analysis using composite interval mapping detected 16 QTL for the six traits in 30-day-old seedlings. Of these 16 QTL, Minghui 63 alleles increased trait values at only two of them. The QTL in the vicinity of R3166 on chromosome 5 simultaneously influenced PH, SDW, MRL, RDW, and TDW in the same direction. Twenty QTL were detected for the same traits in the 40-day-old seedlings. However, at this stage Minghui 63 alleles increased trait values at eight QTL. The QTL linked to R3166 also affected PH, SDW, MRL, RDW, and TDW. Only four QTL were common to the two stages. These results clearly indicate that different genes (QTL) control the same traits during different time intervals. Zhenshan 97 alleles had positive effects during the first 30 days of seedling growth, but thereafter the positive effects of Minghui 63 alleles on seedling growth gradually became more pronounced.     

Six new recombinant inbred populations for the study of quantitative traits in Arabidopsis thaliana

Quantitative approaches are now widely used to study the genetic architecture of complex traits. However, most studies have been conducted in single mapping populations, which sample only a fraction of the natural allelic variation available within a gene pool and can identify only a subset of the loci controlling the traits. To enable the progress towards an understanding of the global genetic architecture of a broad range of complex traits, we have developed and characterised six new Arabidopsis thaliana recombinant inbred populations. To evaluate the utility of these populations for integrating analyses from multiple populations, we identified quantitative trait loci (QTL) controlling flowering time in vernalized plants growing in 16 h days. We used the physical positions of markers to align the linkage maps of our populations with those of six existing populations. We identified seven QTL in genomic locations coinciding with those identified in previous studies and in addition a further eight QTL were identified. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. An erratum to this article can be found at     

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.     

Model for mapping imprinted quantitative trait loci in an inbred F2 design

The role of imprinting in shaping development has been ubiquitously observed in plants, animals, and humans. However, a statistical method that can detect and estimate the effects of imprinted quantitative trait loci (iQTL) over the genome has not been extensively developed. In this article, we propose a maximum likelihood approach for testing and estimating the imprinted effects of iQTL that contribute to variation in a quantitative trait. This approach, implemented with the EM algorithm, allows for a genome-wide scan for the existence of iQTL. This approach was used to reanalyze published data in an F(2) family derived from the LG/S and SM/S mouse strains. Several iQTL that regulate the growth of body weight by expressing paternally inherited alleles were identified. Our approach provides a standard procedure for testing the statistical significance of iQTL involved in the genetic control of complex traits.     

Identification of quantitative trait loci influencing traits related to energy balance in selection and inbred lines of mice.

Energy balance is a complex trait with relevance to the study of human obesity and maintenance energy requirements of livestock. The objective of this study was to identify, using unique mouse models, quantitative trait loci (QTL) influencing traits that contribute to variation in energy balance. Two F2 resource populations were created from lines of mice differing in heat loss measured by direct calorimetry as an indicator of energy expenditure. The HB F2 resource population originated from a cross between a noninbred line selected for high heat loss and an inbred line with low heat loss. Evidence for significant QTL influencing heat loss was found on chromosomes 1, 2, 3, and 7. Significant QTL influencing body weight and percentage gonadal fat, brown fat, liver, and heart were also identified. The LH F2 resource population originated from noninbred lines of mice that had undergone divergent selection for heat loss. Chromosomes 1 and 3 were evaluated. The QTL for heat loss identified on chromosome 1 in the HB population was confirmed in the LH population, although the effect was smaller. The presence of a QTL influencing 6-wk weight was also confirmed. Suggestive evidence for additional QTL influencing heat loss, percentage subcutaneous fat, and percentage heart was found for chromosome 1.     

Quantitative trait loci for cold tolerance of rice recombinant inbred lines in low temperature environments

Low temperature is one of the major environmental stresses in rice cultivation in high-altitude and high-latitude regions. In this study, we cultivated a set of recombinant inbred lines (RIL) derived from Dasanbyeo (indica) / TR22183 (japonica) crosses in Yanji (high-latitude area), Kunming (high-altitude area), Chuncheon (cold water irrigation) and Suwon (normal) to evaluate the main effects of quantitative trait loci (QTL) and epistatic QTL (E-QTL) with regard to their interactions with environments for cold-related traits. Six QTLs for spikelet fertility (SF) were identified in three cold treatment locations. Among them, four QTLs on chromosomes 2, 7, 8, and 10 were validated by several near isogenic lines (NILs) under cold treatment in Chuncheon. A total of 57 QTLs and 76 E-QTLs for nine cold-related traits were identified as distributing on all 12 chromosomes; among them, 19 QTLs and E-QTLs showed significant interactions of QTLs and environments (QEIs). The total phenotypic variation explained by each trait ranged from 13.2 to 29.1% in QTLs, 10.6 to 29.0% in EQTLs, 2.2 to 8.8% in QEIs and 1.0% to 7.7% in E-QTL × environment interactions (E-QEIs). These results demonstrate that epistatic effects and QEIs are important properties of QTL parameters for cold tolerance at the reproductive stage. In order to develop cold tolerant varieties adaptable to wide-ranges of cold stress, a strategy facilitating marker-assisted selection (MAS) is being adopted to accumulate QTLs identified from different environments.