Extremely elongated tomato fruit controlled by four quantitative trait loci with epistatic interactions

Cultivated tomato (Lycopersicon esculentum) encompass a wide range of fruit shape and size variants. This variation can be used to genetically dissect the molecular basis of ovary and fruit morphology. The cultivar Long John displays an extremely elongated fruit phenotype, while the wild relative Lycopersicon pimpinellifolium LA1589 produces fruit that are nearly perfect spheres, typical of wild tomatoes. Quantitative trait mapping of an F2 population between Long John and LA1589 revealed four fruit shape QTLs, located on chromosomes 2, 3, 7 and 11. The primary role of the fruit shape QTL located on chromosome 7, ljfs7, is to control pericarp elongation. The primary role of the fruit shape QTLs on chromosome 2, 3 and 11 (ljfs2, ljfs3 and ljfs11, respectively) is to control pear shape, measured as the eccentricity index. QTL map position and the effect of the loci on fruit shape suggested that ljfs2 and ljfs7 are allelic to the well-studied fruit shape loci ovate and sun, respectively. ljfs3 and ljfs11 map near the previously identified, but less characterized, fruit shape loci fs3.2 and fs11.1, respectively. This result suggests that most of the variation in tomato fruit shape is controlled by a few major QTLs. Although eccentricity and pericarp elongation were largely controlled by independent growth processes, significant interactions were detected between all four fruit shape loci in the control of eccentricity. This indicates that the three eccentricity loci, ljfs2, ljfs3 and ljfs11, epistatically control the same developmental process, while ljfs7 had a pleiotropic effect on eccentricity. Received: 27 March 2001 / Accepted: 7 May 2001     

High-resolution quantitative trait locus mapping reveals sign epistasis controlling ovariole number between two Drosophila species

Identifying the genes underlying genetically complex traits is of fundamental importance for medicine, agriculture, and evolutionary biology. However, the level of resolution offered by traditional quantitative trait locus (QTL) mapping is usually coarse. We analyze here a trait closely related to fitness, ovariole number. Our initial interspecific mapping between Drosophila sechellia (8 ovarioles/ovary) and D. simulans (15 ovarioles/ovary) identified a major QTL on chromosome 3 and a minor QTL on chromosome 2. To refine the position of the major QTL, we selected 1038 additional recombinants in the region of interest using flanking morphological markers (selective phenotyping). This effort generated approximately one recombination event per gene and increased the mapping resolution by approximately seven times. Our study thus shows that using visible markers to select for recombinants can efficiently increase the resolution of QTL mapping. We resolved the major QTL into two epistatic QTL, QTL3a and QTL3b. QTL3a shows sign epistasis: it has opposite effects in two different genetic backgrounds, the presence vs. the absence of the QTL3b D. sechellia allele. This property of QTL3a allows us to reconstruct the probable order of fixation of the QTL alleles during evolution.     

Cytonuclear epistatic quantitative trait locus mapping for plant height and ear height in maize

Plant height (PH) and ear height (EH) are important traits in maize (Zea mays L.) breeding. Previous research has indicated that these traits are influenced by quantitative trait loci (QTL). However, previous studies attempting to identify the genetic bases of PH and EH have ignored the possibility that cytoplasmic effects and cytonuclear interactions may influence these traits. The objectives of this study were to identify the cytonuclear epistatic QTL and to evaluate the contributions of cytoplasm and QTL × cytoplasm interactions to phenotypic variation of PH and EH. A reciprocal mating design was conducted to generate F2 mapping populations comprising 120 F2 plants from the direct cross (JB × Y53) and 120 F2 plants from the reciprocal cross (Y53 × JB). F2:3 mapping populations were further generated with 91 direct F2:3 families and 120 reciprocal F2:3 families (ten plants per family). The PH and EH of the above F2 and F2:3 mapping populations were evaluated in the same field at the same experimental station in 2007 and 2008. A genetic linkage map with 154 microsatellite markers was constructed, which covered 1,735.0 cM of the maize genome with an average marker spacing of 11.3 cM. A joint-analysis method incorporating the cytonuclear interaction mapping approach was proposed and performed to detect cytonuclear interacting QTL affecting PH and EH. We identified six cytonuclear epistatic QTL affecting PH and five affecting EH. The average phenotypic variance explained by the genetic components of the QTL × cytoplasm interaction for each QTL was 18 % for PH and 9 % for EH. In addition, we observed cytoplasmic effects contributing substantially to phenotypic variance, reaching 9 and 40 % of the phenotypic contributions to PH and EH, respectively.     

Quantitative trait locus mapping reveals complex genetic architecture of quantitative virulence in the wheat pathogen Zymoseptoria tritici

We conducted a comprehensive analysis of virulence in the fungal wheat pathogen Zymoseptoria tritici using quantitative trait locus (QTL) mapping. High‐throughput phenotyping based on automated image analysis allowed the measurement of pathogen virulence on a scale and with a precision that was not previously possible. Across two mapping populations encompassing more than 520 progeny, 540 710 pycnidia were counted and their sizes and grey values were measured. A significant correlation was found between pycnidia size and both spore size and number. Precise measurements of percentage leaf area covered by lesions provided a quantitative measure of host damage. Combining these large and accurate phenotypic datasets with a dense panel of restriction site‐associated DNA sequencing (RADseq) genetic markers enabled us to genetically dissect pathogen virulence into components related to host damage and those related to pathogen reproduction. We showed that different components of virulence can be under separate genetic control. Large‐ and small‐effect QTLs were identified for all traits, with some QTLs specific to mapping populations, cultivars and traits and other QTLs shared among traits within the same mapping population. We associated the presence of four accessory chromosomes with small, but significant, increases in several virulence traits, providing the first evidence for a meaningful function associated with accessory chromosomes in this organism. A large‐effect QTL involved in host specialization was identified on chromosome 7, leading to the identification of candidate genes having a large effect on virulence.     

Complex genetic interactions in a quantitative trait locus

Whether in natural populations or between two unrelated members of a species, most phenotypic variation is quantitative. To analyze such quantitative traits, one must first map the underlying quantitative trait loci. Next, and far more difficult, one must identify the quantitative trait genes (QTGs), characterize QTG interactions, and identify the phenotypically relevant polymorphisms to determine how QTGs contribute to phenotype. In this work, we analyzed three Saccharomyces cerevisiae high-temperature growth (Htg) QTGs (MKT1, END3, and RHO2). We observed a high level of genetic interactions among QTGs and strain background. Interestingly, while the MKT1 and END3 coding polymorphisms contribute to phenotype, it is the RHO2 3′UTR polymorphisms that are phenotypically relevant. Reciprocal hemizygosity analysis of the Htg QTGs in hybrids between S288c and ten unrelated S. cerevisiae strains reveals that the contributions of the Htg QTGs are not conserved in nine other hybrids, which has implications for QTG identification by marker-trait association. Our findings demonstrate the variety and complexity of QTG contributions to phenotype, the impact of genetic background, and the value of quantitative genetic studies in S. cerevisiae.     

High-resolution quantitative trait locus mapping for body weight in mice by recombinant progeny testing

A major obstacle to the positional cloning of quantitative trait loci (QTLs) lies in resolving genetic factors whose allelic effects are blurred by environmental and background genetic variation. We investigate a fine-mapping approach that combines the use of an interval-specific congenic strain with progeny testing of recombinants for markers flanking a QTL. We apply the approach to map a murine QTL with an approximately 20% effect on growth rate by progeny testing 39 recombinants in a 12 cM region of the X chromosome. We use a likelihood analysis in an attempt to maximize the information on QTL map location and effect. The major X-linked effect is mapped to an approximately 2 cM region flanked by markers about 5 cM apart, outside which LOD support for the QTL drops extremely steeply by about 80. Nearly unambiguous assignment of the QTL genotypic state is obtained for each recombinant. The resolution of individual recombinants in the region is therefore sufficiently high to facilitate the positional cloning of the locus, although progress has been hampered because the genomic region containing the QTL shows an exceptionally low level of polymorphism in comparison with recent studies.     

棉花数量性状基因定位研究进展

棉花的许多重要性状,包括产量、纤维品质、株型、抗病抗逆性、生理生化等都是数量性状,受遗传和环境因子的共同作用。近年来,随着分子生物学技术的进步,棉花基因组研究得到迅速发展,为棉花数量性状基因（quantitative trait locus,QTL）定位奠定了坚实的基础。概述了近十几年来棉花QTL定位研究及分子标记辅助选择的进展,结合研究实践指出了棉花QTL定位及标记辅助选择存在的问题,并对其发展方向做出了初步探讨。     

番茄果重数量性状基因的研究进展及在遗传学教学中的应用

遗传学发展史上一系列经典的研究案例对学科的发展起了巨大的推动作用,将这些经典案例与教学内容相结合应用到遗传学课程教学中,对学生的科学思维和遗传分析能力是一个很好的训练。番茄果重基因的定位与克隆在数量性状基因座研究中是开创性的工作,完整的体现了植物数量性状基因的研究历程。将其作为一个综合案例应用于遗传学教学,可以生动直观地给学生展示一个精彩的科学发现过程,展现遗传学研究的魅力,激发学生的学习兴趣,收到了很好的教学效果。     

Multiple-trait quantitative trait locus mapping with incomplete phenotypic data

Background

The goal of linkage analysis is to determine the chromosomal location of the gene(s) for a trait of interest such as a common disease. Three-locus linkage analysis is an important case of multi-locus problems. Solutions can be found analytically for the case of triple backcross mating. However, in the present study of linkage analysis and gene mapping some natural inequality restrictions on parameters have not been considered sufficiently, when the maximum likelihood estimates (MLEs) of the two-locus recombination fractions are calculated.

Results

In this paper, we present a study of estimating the two-locus recombination fractions for the phase-unknown triple backcross with two offspring in each family in the framework of some natural and necessary parameter restrictions. A restricted expectation-maximization (EM) algorithm, called REM is developed. We also consider some extensions in which the proposed REM can be taken as a unified method.

Conclusion

Our simulation work suggests that the REM performs well in the estimation of recombination fractions and outperforms current method. We apply the proposed method to a published data set of mouse backcross families.     

More about quantitative trait locus mapping with diallel designs

We present a general regression-based method for mapping quantitative trait loci (QTL) by combining different populations derived from diallel designs. The model expresses, at any map position, the phenotypic value of each individual as a function of the specific-mean of the population to which the individual belongs, the additive and dominance effects of the alleles carried by the parents of that population and the probabilities of QTL genotypes conditional on those of neighbouring markers. Standard linear model procedures (ordinary or iteratively reweighted least-squares) are used for estimation and test of the parameters.     

The X chromosome in quantitative trait locus mapping

The X chromosome requires special treatment in the mapping of quantitative trait loci (QTL). However, most QTL mapping methods, and most computer programs for QTL mapping, have focused exclusively on autosomal loci. We describe a method for appropriate treatment of the X chromosome for QTL mapping in experimental crosses. We address the important issue of formulating the null hypothesis of no linkage appropriately. If the X chromosome is treated like an autosome, a sex difference in the phenotype can lead to spurious linkage on the X chromosome. Further, the number of degrees of freedom for the linkage test may be different for the X chromosome than for autosomes, and so an X chromosome-specific significance threshold is required. To address this issue, we propose a general procedure to obtain chromosome-specific significance thresholds that controls the genomewide false positive rate at the desired level. We apply our methods to data on gut length in a large intercross of mice carrying the Sox10Dom mutation, a model of Hirschsprung disease. We identified QTL contributing to variation in gut length on chromosomes 5 and 18. We found suggestive evidence of linkage to the X chromosome, which would be viewed as strong evidence of linkage if the X chromosome was treated as an autosome. Our methods have been implemented in the package R/qtl.     

High-resolution fine mapping and fluorescence in situ hybridization analysis of sun, a locus controlling tomato fruit shape, reveals a region of the tomato genome prone to DNA rearrangements

The locus sun on the short arm of tomato chromosome 7 controls morphology of the fruit. Alleles from wild relatives impart a round shape, while alleles from certain cultivated varieties impart an oval shape typical of roma-type tomatoes. We fine mapped the locus in two populations and investigated the genome organization of the region spanning and flanking sun. The first high-resolution genetic map of the sun locus was constructed using a nearly isogenic F(2) population derived from a cross between Lycopersicon pennellii introgression line IL7-4 and L. esculentum cv Sun1642. The mapping combined with results from pachytene FISH experiments demonstrated that the top of chromosome 7 is inverted in L. pennellii accession LA716. sun was located close to the chromosomal breakpoint and within the inversion, thereby precluding map-based cloning of the gene using this population. The fruit-shape locus was subsequently fine mapped in a population derived from a cross between L. esculentum Sun1642 and L. pimpinellifolium LA1589. Chromosome walking using clones identified from several large genomic insert libraries resulted in two noncontiguous contigs flanking sun. Fiber-FISH analysis showed that distance between the two contigs measured 68 kb in L. esculentum Sun1642 and 38 kb in L. pimpinellifolium LA1589, respectively. The sun locus mapped between the two contigs, suggesting that allelic variation at this locus may be due to an insertion/deletion event. The results demonstrate that sun is located in a highly dynamic region of the tomato genome.     

High-resolution association mapping of quantitative trait loci: a population-based approach

In this article, population-based regression models are proposed for high-resolution linkage disequilibrium mapping of quantitative trait loci (QTL). Two regression models, the "genotype effect model" and the "additive effect model," are proposed to model the association between the markers and the trait locus. The marker can be either diallelic or multiallelic. If only one marker is used, the method is similar to a classical setting by Nielsen and Weir, and the additive effect model is equivalent to the haplotype trend regression (HTR) method by Zaykin et al. If two/multiple marker data with phase ambiguity are used in the analysis, the proposed models can be used to analyze the data directly. By analytical formulas, we show that the genotype effect model can be used to model the additive and dominance effects simultaneously; the additive effect model takes care of the additive effect only. On the basis of the two models, F-test statistics are proposed to test association between the QTL and markers. By a simulation study, we show that the two models have reasonable type I error rates for a data set of moderate sample size. The noncentrality parameter approximations of F-test statistics are derived to make power calculation and comparison. By a simulation study, it is found that the noncentrality parameter approximations of F-test statistics work very well. Using the noncentrality parameter approximations, we compare the power of the two models with that of the HTR. In addition, a simulation study is performed to make a comparison on the basis of the haplotype frequencies of 10 SNPs of angiotensin-1 converting enzyme (ACE) genes.     

Substitution mapping of dth1.1, a flowering-time quantitative trait locus (QTL) associated with transgressive variation in rice, reveals multiple sub-QTL

A quantitative trait locus (QTL), dth1.1, was associated with transgressive variation for days to heading in an advanced backcross population derived from the Oryza sativa variety Jefferson and an accession of the wild rice relative Oryza rufipogon. A series of near-isogenic lines (NILs) containing different O. rufipogon introgressions across the target region were constructed to dissect dth1.1 using substitution mapping. In contrast to the late-flowering O. rufipogon parent, O. rufipogon alleles in the substitution lines caused early flowering under both short- and long-day lengths and provided evidence for at least two distinct sub-QTL: dth1.1a and dth1.1b. Potential candidate genes underlying these sub-QTL include genes with sequence similarity to Arabidopsis GI, FT, SOC1, and EMF1, and Pharbitis nil PNZIP. Evidence from families with nontarget O. rufipogon introgressions in combination with dth1.1 alleles also detected an early flowering QTL on chromosome 4 and a late-flowering QTL on chromosome 6 and provided evidence for additional sub-QTL in the dth1.1 region. The availability of a series of near-isogenic lines with alleles introgressed from a wild relative of rice provides an opportunity to better understand the molecular basis of transgressive variation in a quantitative trait.     

A penalized likelihood method for mapping epistatic quantitative trait Loci with one-dimensional genome searches

Epistasis is a common and important phenomenon, as indicated by results from a number of recent experiments. Unfortunately, the discovery of epistatic quantitative trait loci (QTL) is difficult since one must search for multiple QTL simultaneously in two or more dimensions. Such a multidimensional search necessitates many statistical tests, and a high statistical threshold must be adopted to avoid false positives. Furthermore, the large number of (interaction) parameters in comparison with the number of observations results in a serious danger of overfitting and overinterpretation of the data. In this article we present a new statistical framework for mapping epistasis in inbred line crosses. It is based on reducing the high dimensionality of the problem in two ways. First, epistatic QTL are mapped in a one-dimensional genome scan for high interactions between QTL and the genetic background. Second, the dimension of the search is bounded by penalized likelihood methods. We use simulated backcross data to illustrate the new approach.     

High-resolution mapping of quantitative trait loci by selective recombinant genotyping

Selective recombinant genotyping (SRG) is a three-stage procedure for high-resolution mapping of a QTL that has previously been mapped to a known confidence interval (target C.I.). In stage 1, a large mapping population is accessed and phenotyped, and a proportion, P, of the high and low tails is selected. In stage 2, the selected individuals are genotyped for a pair of markers flanking the target C.I., and a group of R individuals carrying recombinant chromosomes in the target interval are identified. In stage 3, the recombinant individuals are genotyped for a set of M markers spanning the target C.I. Extensive simulations showed that: (1) Standard error of QTL location (SEQTL) decreased when QTL effect (d) or population size (N) increased, but was constant for given "power factor" (PF = d(2)N); (2) increasing the proportion selected in the tails beyond 0.25 had only a negligible effect on SEQTL; and (3) marker spacing in the target interval had a remarkably powerful effect on SEQTL, yielding a reduction of up to 10-fold in going from highest (24 cM) to lowest (0.29 cM) spacing at given population size and QTL effect. At the densest marker spacing, SEQTL of 1.0-0.06 cM were obtained at PF = 500-16,000. Two new genotyping procedures, the half-section algorithm and the golden section/half-section algorithm, allow the equivalent of complete haplotyping of the target C.I. in the recombinant individuals to be achieved with many fewer data points than would be required by complete individual genotyping.     

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and body mass index. Despite the fact that these traits change throughout life they are commonly analyzed only at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modeled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF-based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.     

High-resolution mapping and functional analysis of se2.1: a major stigma exsertion quantitative trait locus associated with the evolution from allogamy to autogamy in the genus Lycopersicon

The degree to which stigmas are exserted above the stamen in flowers is a key determinant of cross-pollination (and hence allogamy) in many plant species. Most species in the genus Lycopersicon are obligate or facultative outcrossers and bear flowers with highly exserted stigmas. In contrast, the cultivated tomato (Lycopersicon esculentum) bears flowers with flush or inserted stigmas promoting self-fertilization. It has been observed that a major QTL, se2.1, on chromosome 2 is responsible for a large portion of phenotypic variation for this trait and that mutation(s) at this locus were likely involved in the evolution from allogamy to autogamy in this genus. To understand the genetic and molecular basis of stigma exsertion, we have conducted a high-resolution mapping at the chromosome region harboring the se2.1 QTL. The results indicate that this is a compound locus, comprising at least five tightly linked genes, one controlling style length, three controlling stamen length, and the other affecting anther dehiscence, a taxonomic character used to distinguish Lycopersicon species from other solanaceous species. This cluster of genes may represent the vestiges of an ancient coadapted gene complex in controlling mating behavior.