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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.

Alleles↗

A statistically robust variance-components approach for quantitative trait linkage analysis.

Previously we showed (Wang, Guerra & Cohen 1998) that a statistically robust version of the Haseman & Elston (1972) sib-pair method greatly increased power to detect linkage in the presence of outliers. In this paper we report on M-estimation to accommodate outliers in the variance-components approach to linkage analysis developed by Amos (1994). Simulations show that in the presence of outliers the robust variance-components approach provides substantially greater power, more precise estimation of heritabilities, and better false-positive rates than the original Gaussian based approach. In the absence of outliers the performance of the robust variance-components approach is similar to that of the Gaussian based approach. For illustration we apply the method to two well characterized lipoprotein systems.

Alleles↗

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population.

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.

Adipose Tissue↗

Hypothesis testing for the genetic background of quantitative traits.

The testing of Bayesian point null hypotheses on variance component models have resulted in a tough assigmment for which no clear and generally accepted method exists. In this work we present what we believe is a succeeding approach to such a task. It is based on a simple reparameterization of the model in terms of the total variance and the proportion of the additive genetic variance with respect to it, as well as on the explicit inclusion on the prior probability of a discrete component at origin. The reparameterization was used to bypass an arbitrariness related to the impropriety of uninformative priors onto unbounded variables while the discrete component was necessary to overcome the zero probability assigned to sets of null measure by the usual continuous variable models. The method was tested against computer simulations with appealing results.

Algorithms↗

Gene mapping of SEZ group genes and determination of pentylenetetrazol susceptible quantitative trait loci in the mouse chromosome.

Gene mapping of the newly discovered SEZ genes (seizure-related genes) in the mouse was performed by linkage analysis. SEZ6 was on chromosome 11, SEZ12 on chromosome 16, SEZ15 on chromosome 3 and SEZ17 (PTZ17) on chromosome 18. The mouse chromosomal locus related to high susceptibility to pentylenetetrazol (PTZ) was also determined by linkage analysis using the recombinant inbred mouse, BXD (C57BLxDBA). A significant level of PTZ susceptibility was found on chromosome 2. Chromosomal loci of the newly discovered SEZ genes were not coincident with the significant chromosomal loci to PTZ susceptibility. Since epilepsy is assumed to be a disease syndrome which is probably manifested by abnormal expression of multifocal genes, determination of the role of each chromosomal locus in the provocation of seizure activity is important.

Animals↗

A general statistical framework for mapping quantitative trait loci in nonmodel systems: issue for characterizing linkage phases.

Because of uncertainty about linkage phases of founders, linkage mapping in nonmodel, outcrossing systems using molecular markers presents one of the major statistical challenges in genetic research. In this article, we devise a statistical method for mapping QTL affecting a complex trait by incorporating all possible QTL-marker linkage phases within a mapping framework. The advantage of this model is the simultaneous estimation of linkage phases and QTL location and effect parameters. These estimates are obtained through maximum-likelihood methods implemented with the EM algorithm. Extensive simulation studies are performed to investigate the statistical properties of our model. In a case study from a forest tree, this model has successfully identified a significant QTL affecting wood density. Also, the probability of the linkage phase between this QTL and its flanking markers is estimated. The implications of our model and its extension to more general circumstances are discussed.

Chromosome Mapping↗

A pedigree partitioning approach to quantitative trait loci mapping of IgE serum level in the GAW12 Hutterite data.

We present a semi-automatic method that uses principles from factor analysis to subdivide large pedigrees into smaller, non-overlapping sub-pedigrees. Application of our method to the Genetic Analysis Workshop 12 Hutterite pedigree yielded 12 sub-pedigrees that were used to carry out a genome-wide linkage scan for IgE serum level in SOLAR. Two-point analyses resulted in strong evidence for linkage to two marker loci on chromosome 1, D1S3723 (lod = 3.70) and D1S534 (lod = 3.58). Multipoint analysis resulted in a maximum lod of 4.58 on chromosome 1 at 143 cM. After extending the two pedigrees that contributed the most evidence for linkage, the maximum lod score decreased to 4.18, with most of the evidence for linkage due to a single large sub-pedigree.

Adult↗

Regional heterogeneity and gene flow maintain variance in a quantitative trait within populations of lodgepole pine.

Genetic variation is of fundamental importance to biological evolution, yet we still know very little about how it is maintained in nature. Because many species inhabit heterogeneous environments and have pronounced local adaptations, gene flow between differently adapted populations may be a persistent source of genetic variation within populations. If this migration-selection balance is biologically important then there should be strong correlations between genetic variance within populations and the amount of heterogeneity in the environment surrounding them. Here, we use data from a long-term study of 142 populations of lodgepole pine (Pinus contorta) to compare levels of genetic variation in growth response with measures of climatic heterogeneity in the surrounding region. We find that regional heterogeneity explains at least 20% of the variation in genetic variance, suggesting that gene flow and heterogeneous selection may play an important role in maintaining the high levels of genetic variation found within natural populations.

Climate↗

Identification of quantitative trait loci controlling levels of radiation-induced thymocyte apoptosis in mice.

Thymocyte apoptosis levels are higher in C57BL/6J mice than in C3Hf/Kam mice. Low-dose irradiation increases the numbers of thymocytes undergoing apoptosis, but the strain difference persists. We mapped three loci controlling radiation-induced thymocyte apoptosis levels in F2 intercross progeny of these strains. The strongest association of a genomic region with an apoptosis level occurred in a region of chromosome 11 known to harbor a locus (or loci) important in the pathogenesis of several rodent models of autoimmune disease. Additional loci influencing radiation-induced thymocyte apoptosis were identified on chromosomes 9 and 16. The genetic polymorphisms underlying these loci may have an evolutionary role in fine-tuning the apoptotic response in T cells and may be important in the etiology of lymphoproliferative disorders and autoimmunity.

Animals↗

A mixed-model approach to mapping quantitative trait loci in barley on the basis of multiple environment data.

In this article, I propose a mixed-model method to detect QTL with significant mean effect across environments and to characterize the stability of effects across multiple environments. I demonstrate the method using the barley dataset by the North American Barley Genome Mapping Project. The analysis raises the need for mixed modeling in two different ways. First, it is reasonable to regard environments as a random sample from a population of target environments. Thus, environmental main effects and QTL-by-environment interaction effects are regarded as random. Second, I expect a genetic correlation among pairs of environments caused by undetected QTL. I show how random QTL-by-environment effects as well as genetic correlations are straightforwardly handled in a mixed-model framework. The main advantage of this method is the ability to assess the stability of QTL effects. Moreover, the method allows valid statistical inferences regarding average QTL effects.

Crosses, Genetic↗

Positional cloning of the major quantitative trait locus underlying lung tumor susceptibility in mice.

Pulmonary adenoma susceptibility 1 (Pas1), located on chromosome 6, is the major locus affecting inherited predisposition to lung tumor development in mice. We have fine mapped the Pas1 locus to a region of approximately 0.5 megabases by using congenic strains of mice, constructed by placing the Pas1 region of chromosome 6 from A/J mice onto the genetic background of C57BL/6J mice. Systematic characterization of Pas1 candidates establishes the Las1 (lung adenoma susceptibility 1) and Kras2 (Kirsten rat sarcoma oncogene 2) genes as primary candidates for the Pas1 locus. Clearly, Kras2 affects lung tumor progression only, and Las1 is likely to affect lung tumor multiplicity.

Adenoma↗

A large-insert porcine library with sevenfold genome coverage: a tool for positional cloning of candidate genes for major quantitative traits.

A porcine genomic bacterial artificial chromosome (BAC) library was constructed by cloning partial EcoRI-digested high-molecular-weight DNA from a Korean native boar into the EcoRI site of the pBACe3.6 vector. The library consists of about 165,000 clones with an average insert size of 125 kb, representing about seven genome equivalents of coverage. About 130,000 clones (corresponding to fivefold genome coverage) were arrayed in 14 superpools which were organized as four dimensional pools. The library was further characterized by PCR screening of 38 microsatellite probes. An average of 4.84 positive clones were selected per marker. This indicates that the library is unbiased and will be useful for initiating fine scale physical mapping of major QTL in pigs. The library is being used to isolate specific clones by screening with type I and type II marker clones located in the QTL region affecting intramuscular fat content on SSC6.

Animals↗

Mapping quantitative trait loci in the case of a spike in the phenotype distribution.

A common departure from the usual normality assumption in QTL mapping concerns a spike in the phenotype distribution. For example, in measurements of tumor mass, some individuals may exhibit no tumors; in measurements of time to death after a bacterial infection, some individuals may recover from the infection and fail to die. If an appreciable portion of individuals share a common phenotype value (generally either the minimum or the maximum observed phenotype), the standard approach to QTL mapping can behave poorly. We describe several alternative approaches for QTL mapping in the case of such a spike in the phenotype distribution, including the use of a two-part parametric model and a nonparametric approach based on the Kruskal-Wallis test. The performance of the proposed procedures is assessed via computer simulation. The procedures are further illustrated with data from an intercross experiment to identify QTL contributing to variation in survival of mice following infection with Listeria monocytogenes.

Computer Simulation↗

Effects of quantitative trait loci on chromosomes 1, 2, 4, and 7 on growth, carcass, and meat quality traits in backcross Meishan x Large White pigs.

The aim of this work was to estimate whether genetic dissection of QTL on chromosomes 1, 2, 4, and 7, detected in an F2 Meishan x Large White population, can be achieved with a recombinant back-cross progeny test approach. For this purpose, a first generation of backcross (BC1) was produced by using frozen semen of F1 Large White x Meishan boars with Large White females. Four BC1 boars were selected because of their heterozygosity for at least 1 of the 4 regions. The BC1 boars were crossed with Large White sows, and the resulting BC2 offspring were measured for several growth and body composition traits. Contrary to the F2 animals, BC2 animals were also measured for meat quality traits in adductor, gluteus superficialis (GS), longissimus dorsi, and biceps femoris (BF) muscles. Each BC1 boar was tested for a total of 39 traits and for the 4 regions with statistical interval mapping analyses. The QTL effects obtained in BC1 families showed some differences compared with those described in F1 families. However, we confirmed QTL effects for growth in the SW1301-SW2512 markers interval on chromosome 1 and also for body composition in the SW1828-SW2512 markers interval on chromosome 1, in the SW2443-SWR783 markers interval on chromosome 2, and in the SW1369-SW632 markers interval on chromosome 7. In addition, we detected new QTL for growth traits on chromosome 2 and for meat quality traits on chromosomes 1 and 2. Growth of animals from weaning to the end of the test was influenced by the IGF2 gene region on chromosome 2. Concerning meat quality, ultimate pH of adductor, longissimus dorsi, and BF were affected by the interval delimited by UMNP3000 and SW2512 markers on chromosome 1, and a* of GS, L* of BF, and water-holding capacity of GS were affected by QTL located between marker loci SW2443 and SWR783 on chromosome 2. Recombinant progeny testing appeared to be a suitable strategy for the genetic dissection of the QTL investigated.

Adipose Tissue↗

Large-scale, multibreed, multitrait analyses of quantitative trait loci experiments: the case of porcine X chromosome.

A QTL analysis of multibreed experiments (i.e., crossed populations involving more than two founder breeds) offers clear advantages over classical two-breed crosses, among them increased power and a more comprehensive coverage of the total genetic variability in the species. An alternative to designed multibreed crosses is to reanalyze jointly several experiments involving different breeds. We report a multibreed, multitrait QTL analysis of SSCX that involves five different crosses, six breeds, and almost 3,000 genotyped individuals using a truly multibreed strategy to allow for any number of founder breed origins. Traits analyzed were growth, fat thickness, carcass length, and shoulder and ham weights. Generally, the joint analysis resulted in more significant QTL than the single-experiment analyses. We show that the QTL for fatness, which is highly significant (nominal P < 10(-43)), is of Asiatic origin (Meishan). The next most significant QTL (nominal P < 10(-15)) affected ham weight and seems to be segregating only between Large White and the rest of the breeds. A multitrait, multi-QTL analysis suggests that these are two distinct loci. Additionally, a locus segregating only between Iberian and Landrace affects live weight. The advantages of joint, multibreed analyses clearly outweigh their potential risks.

Adipose Tissue↗

Quantitative trait loci and molecular markers associated with wheat allelopathy.

Wheat ( Triticum aestivum L.) has been examined for allelopathic potential against annual ryegrass ( Lolium rigidum). The bioassay technique, 'equal-compartment-agar-method', was employed to evaluate seedling allelopathy in a doubled-haploid (DH) population derived from cv Sunco (weakly allelopathic) and cv Tasman (strongly allelopathic). A significant difference in allelopathic activity was found among the DH lines, which inhibited the root length of ryegrass across a range from 23.7 to 88.3%. The phenotypic data showed that wheat allelopathic activity was distributed normally within this DH population and a substantial transgressive segregation for seedling allelopathic activity was also found. Analysis of restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP) and microsatellite (SSRs) markers identified two major QTLs on chromosome 2B associated with wheat allelopathy. The linkage analysis of genetic markers and the QTLs may improve genetic gains for the allelopathic activity through marker-assisted selection in wheat breeding. The development of wheat allelopathic cultivars could reduce the over-reliance of weed control on synthetic herbicides.

Genetic Markers↗

Mapping of quantitative trait loci for salt tolerance at the seedling stage in rice.

Salt tolerance was evaluated at the young seedling stage of rice (Oryza sativa L.) using recombinant inbred lines (MG RILs) from a cross between Milyang 23 (japonica/indica) and Gihobyeo (japonica). 22 of 164 MG RILs were classified as tolerant with visual scores of 3.5-5.0 in 0.7% NaCl. Interval mapping of QTLs related to salt tolerance was conducted on the basis of the visual scores at the young seedling stage. Two QTLs, qST1 and qST3, conferring salt tolerance, were detected on chromosome 1 and 3, respectively, and the total phenotypic variance explained by the two QTLs was 36.9% in the MG RIL population. qST1 was the major QTL explaining 27.8% of the total phenotypic variation. qST1 was flanked by Est12-RZ569A, and qST3 was flanked by RG179-RZ596. The detection of new QTLs associated with salt tolerance will provide important information for the functional analysis of rice salt tolerance.

Genotype↗

Detection and localization of quantitative trait loci affecting fatness in broilers.

A cross between 2 genetically different outcross broiler dam lines, originating from the White Plymouth Rock breed, was used to produce a large 3-generation broiler population. This population was used to detect and localize QTL affecting fatness in chicken. Twenty full-sib birds in generation 1 and 456 full-sib birds in generation 2 were typed for microsatellite markers, and phenotypic observations were collected for 3 groups of generation 3 birds (approximately 1,800 birds per group). Body weight, abdominal fat weight, and percentage abdominal fat was recorded at the age of 7, 9, and 10 wk. To study the presence of QTL, an across-family weighted regression interval mapping approach was used in a full-sib QTL analysis. Genotypes from 410 markers mapped on 25 chromosomes were available. For the 3 traits, 26 QTL were found for 18 regions on 12 chromosomes. Two genomewise significant QTL (P < 0.05) were detected, one for percentage abdominal fat at the age of 10 wk on chicken chromosome 1 at 241 cM (MCW0058 to MCW0101) with a test statistic of 2.75 and the other for BW at the age of 10 wk on chicken chromosome 13 at 9 cM (MCW0322 to MCW0110) with a test statistic of 2.77. Significance levels were obtained using the permutation test. Multiple suggestive QTL were found on chromosomes 1, 2, 4, 13, 15, and 18, whereas chromosomes 3, 7, 10, 11, 14, and 27 had a single suggestive QTL.

Abdomen↗