Journal articles on the topic 'QTL (Quantitative trait locus/loci) mapping'
To see the other types of publications on this topic, follow the link: QTL (Quantitative trait locus/loci) mapping.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'QTL (Quantitative trait locus/loci) mapping.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Xu, Shizhong, and Zhiqiu Hu. "Mapping Quantitative Trait Loci Using Distorted Markers." International Journal of Plant Genomics 2009 (February 21, 2009): 1–11. http://dx.doi.org/10.1155/2009/410825.
Full textAbstract:
Quantitative trait locus (QTL) mapping is usually performed using markers that follow a Mendelian segregation ratio. We developed a new method of QTL mapping that can use markers with segregation distortion (non-Mendelian markers). An EM (expectation-maximization) algorithm is used to estimate QTL and SDL (segregation distortion loci) parameters. The joint analysis of QTL and SDL is particularly useful for selective genotyping. Application of the joint analysis is demonstrated using a real life data from a wheat QTL mapping experiment.
2
Xu, Shizhong, and William R. Atchley. "Mapping Quantitative Trait Loci for Complex Binary Diseases Using Line Crosses." Genetics 143, no. 3 (July 1, 1996): 1417–24. http://dx.doi.org/10.1093/genetics/143.3.1417.
Full textAbstract:
Abstract A composite interval gene mapping procedure for complex binary disease traits is proposed in this paper. The binary trait of interest is assumed to be controlled by an underlying liability that is normally distributed. The liability is treated as a typical quantitative character and thus described by the usual quantitative genetics model. Translation from the liability into a binary (disease) phenotype is through the physiological threshold model. Logistic regression analysis is employed to estimate the effects and locations of putative quantitative trait loci (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). Simulation studies show that properties of this mapping procedure mimic those of the composite interval mapping for normally distributed data. Potential utilization of the QTL mapping procedure for resolving alternative genetic models (e.g., single- or two-trait-locus model) is discussed.
3
Tsilo, T. J., J. B. Ohm, G. A. Hareland, S. Chao, and J. A. Anderson. "Quantitative trait loci influencing end-use quality traits of hard red spring wheat breeding lines." Czech Journal of Genetics and Plant Breeding 47, Special Issue (October 20, 2011): S190—S195. http://dx.doi.org/10.17221/3279-cjgpb.
Full textAbstract:
Wheat bread-making quality is influenced by a complex group of traits including dough visco-elastic characteristics. In this study, quantitative trait locus/loci (QTL) mapping and analysis were conducted for endosperm polymeric proteins together with dough mixing strength and bread-making properties in a population of 139 (MN98550 × MN99394) recombinant inbred lines that was evaluated at three environments in 2006. Eleven chromosome regions were associated with endosperm polymeric proteins, explaining 4.2–31.8% of the phenotypic variation. Most of these polymeric proteins QTL coincided with several QTL for dough-mixing strength and bread-making properties. Major QTL clusters were associated with the low-molecular weight glutenin gene Glu-A3, the two high-molecular weight glutenin genes Glu-B1 and Glu-D1, and two regions on chromosome 6D. Alleles at these QTL clusters have previously been proven useful for wheat quality except one of the 6D QTL clusters.
4
Ungerer, Mark C., Solveig S. Halldorsdottir, Jennifer L. Modliszewski, Trudy F. C. Mackay, and Michael D. Purugganan. "Quantitative Trait Loci for Inflorescence Development in Arabidopsis thaliana." Genetics 160, no. 3 (March 1, 2002): 1133–51. http://dx.doi.org/10.1093/genetics/160.3.1133.
Full textAbstract:
Abstract Variation in inflorescence development patterns is a central factor in the evolutionary ecology of plants. The genetic architectures of 13 traits associated with inflorescence developmental timing, architecture, rosette morphology, and fitness were investigated in Arabidopsis thaliana, a model plant system. There is substantial naturally occurring genetic variation for inflorescence development traits, with broad sense heritabilities computed from 21 Arabidopsis ecotypes ranging from 0.134 to 0.772. Genetic correlations are significant for most (64/78) pairs of traits, suggesting either pleiotropy or tight linkage among loci. Quantitative trait locus (QTL) mapping indicates 47 and 63 QTL for inflorescence developmental traits in Ler × Col and Cvi × Ler recombinant inbred mapping populations, respectively. Several QTL associated with different developmental traits map to the same Arabidopsis chromosomal regions, in agreement with the strong genetic correlations observed. Epistasis among QTL was observed only in the Cvi × Ler population, and only between regions on chromosomes 1 and 5. Examination of the completed Arabidopsis genome sequence in three QTL regions revealed between 375 and 783 genes per region. Previously identified flowering time, inflorescence architecture, floral meristem identity, and hormone signaling genes represent some of the many candidate genes in these regions.
5
REBAÏ, AHMED, and BRUNO GOFFINET. "More about quantitative trait locus mapping with diallel designs." Genetical Research 75, no. 2 (April 2000): 243–47. http://dx.doi.org/10.1017/s0016672399004358.
Full textAbstract:
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.
6
Jannink, Jean-Luc, and Ritsert Jansen. "Mapping Epistatic Quantitative Trait Loci With One-Dimensional Genome Searches." Genetics 157, no. 1 (January 1, 2001): 445–54. http://dx.doi.org/10.1093/genetics/157.1.445.
Full textAbstract:
AbstractThe 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.
7
Paran, I., I. L. Goldman, and D. Zamir. "Morphological Trait QTL Mapping in Tomato Recombinant Inbred Line Population." HortScience 30, no. 4 (July 1995): 788D—788. http://dx.doi.org/10.21273/hortsci.30.4.788d.
Full textAbstract:
Quantitative trait loci influencing morphological traits were identified by restriction fragment length polymorphism (RFLP) analysis in a population of recombinant inbred lines (RIL) derived from a cross of the cultivated tomato (Lycopersicon esculentum) with a related wild species (L. cheesmanii). One-hundred-thirty-two polymorphic RFLP loci spaced throughout the tomato genome were scored for 97 RIL families. Morphological traits, including plant height, fresh weight, node number, first flower-bearing node, leaf length at nodes three and four, and number of branches, were measured in replicated trials during 1991, 1992, and 1993. Significant (P ≤ 0.01 level) quantitative trait locus (QTL) associations of marker loci were identified for each trait. Lower plant height, more branches, and shorter internode length were generally associated with RFLP alleles from the L. cheesmanii parent. QTL with large effects on a majority of the morphological traits measured were detected at chromosomes 2, 3, and 4. Large additive effects were measured at significant marker loci for many of the traits measured. Several marker loci exhibited significant associations with numerous morphological traits, suggesting their possible linkage to genes controlling growth and development processes in Lycopersicon.
8
Juenger, Thomas, Michael Purugganan, and Trudy F. C. Mackay. "Quantitative Trait Loci for Floral Morphology in Arabidopsis thaliana." Genetics 156, no. 3 (November 1, 2000): 1379–92. http://dx.doi.org/10.1093/genetics/156.3.1379.
Full textAbstract:
Abstract A central question in biology is how genes control the expression of quantitative variation. We used statistical methods to estimate genetic variation in eight Arabidopsis thaliana floral characters (fresh flower mass, petal length, petal width, sepal length, sepal width, long stamen length, short stamen length, and pistil length) in a cosmopolitan sample of 15 ecotypes. In addition, we used genome-wide quantitative trait locus (QTL) mapping to evaluate the genetic basis of variation in these same traits in the Landsberg erecta × Columbia recombinant inbred line population. There was significant genetic variation for all traits in both the sample of naturally occurring ecotypes and in the Ler × Col recombinant inbred line population. In addition, broad-sense genetic correlations among the traits were positive and high. A composite interval mapping (CIM) analysis detected 18 significant QTL affecting at least one floral character. Eleven QTL were associated with several floral traits, supporting either pleiotropy or tight linkage as major determinants of flower morphological integration. We propose several candidate genes that may underlie these QTL on the basis of positional information and functional arguments. Genome-wide QTL mapping is a promising tool for the discovery of candidate genes controlling morphological development, the detection of novel phenotypic effects for known genes, and in generating a more complete understanding of the genetic basis of floral development.
9
WAYNE, M. L., J. B. HACKETT, C. L. DILDA, S. V. NUZHDIN, E. G. PASYUKOVA, and T. F. C. MACKAY. "Quantitative trait locus mapping of fitness-related traits in Drosophila melanogaster." Genetical Research 77, no. 1 (February 2001): 107–16. http://dx.doi.org/10.1017/s0016672300004894.
Full textAbstract:
We examined the genetic architecture of four fitness-related traits (reproductive success, ovariole number, body size and early fecundity) in a panel of 98 Oregon-R × 2b3 recombinant inbred lines (RILs). Highly significant genetic variation was observed in this population for female, but not male, reproductive success. The cross-sex genetic correlation for reproductive success was 0·20, which is not significantly different from zero. There was significant genetic variation segregating in this cross for ovariole number, but not for body size or early fecundity. The RILs were genotyped for cytological insertion sites of roo transposable elements, yielding 76 informative markers with an average spacing of 3·2 cM. Quantitative trait loci (QTL) affecting female reproductive success and ovariole number were mapped using a composite interval mapping procedure. QTL for female reproductive success were located at the tip of the X chromosome between markers at cytological locations 1B and 3E; and on the left arm of chromosome 2 in the 30D–38A cytological region. Ovariole number QTL mapped to cytological intervals 62D–69D and 98A–98E, both on the third chromosome. The regions harbouring QTL for female reproductive success and ovariole number were also identified as QTL for longevity in previous studies with these lines.
10
Li, Jiahan, Kiranmoy Das, Guifang Fu, Chunfa Tong, Yao Li, Christian Tobias, and Rongling Wu. "EM Algorithm for Mapping Quantitative Trait Loci in Multivalent Tetraploids." International Journal of Plant Genomics 2010 (January 5, 2010): 1–10. http://dx.doi.org/10.1155/2010/216547.
Full textAbstract:
Multivalent tetraploids that include many plant species, such as potato, sugarcane, and rose, are of paramount importance to agricultural production and biological research. Quantitative trait locus (QTL) mapping in multivalent tetraploids is challenged by their unique cytogenetic properties, such as double reduction. We develop a statistical method for mapping multivalent tetraploid QTLs by considering these cytogenetic properties. This method is built in the mixture model-based framework and implemented with the EM algorithm. The method allows the simultaneous estimation of QTL positions, QTL effects, the chromosomal pairing factor, and the degree of double reduction as well as the assessment of the estimation precision of these parameters. We used simulated data to examine the statistical properties of the method and validate its utilization. The new method and its software will provide a useful tool for QTL mapping in multivalent tetraploids that undergo double reduction.
11
Zou, Fei, Brian S. Yandell, and Jason P. Fine. "Rank-Based Statistical Methodologies for Quantitative Trait Locus Mapping." Genetics 165, no. 3 (November 1, 2003): 1599–605. http://dx.doi.org/10.1093/genetics/165.3.1599.
Full textAbstract:
Abstract This article addresses the identification of genetic loci (QTL and elsewhere) that influence nonnormal quantitative traits with focus on experimental crosses. QTL mapping is typically based on the assumption that the traits follow normal distributions, which may not be true in practice. Model-free tests have been proposed. However, nonparametric estimation of genetic effects has not been studied. We propose an estimation procedure based on the linear rank test statistics. The properties of the new procedure are compared with those of traditional likelihood-based interval mapping and regression interval mapping via simulations and a real data example. The results indicate that the nonparametric method is a competitive alternative to the existing parametric methodologies.
12
KEIGHTLEY, PETER D., and SARA A. KNOTT. "Testing the correspondence between map positions of quantitative trait loci." Genetical Research 74, no. 3 (December 1999): 323–28. http://dx.doi.org/10.1017/s0016672399004176.
Full textAbstract:
There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.
13
Korol, A. B., Y. I. Ronin, and V. M. Kirzhner. "Interval mapping of quantitative trait loci employing correlated trait complexes." Genetics 140, no. 3 (July 1, 1995): 1137–47. http://dx.doi.org/10.1093/genetics/140.3.1137.
Full textAbstract:
Abstract An approach to increase the resolution power of interval mapping of quantitative trait (QT) loci is proposed, based on analysis of correlated trait complexes. For a given set of QTs, the broad sense heritability attributed to a QT locus (QTL) (say, A/a) is an increasing function of the number of traits. Thus, for some traits x and y, H(xy)2(A/a) > or = H(x)2(A/a). The last inequality holds even if y does not depend on A/a at all, but x and y are correlated within the groups AA, Aa and aa due to nongenetic factors and segregation of genes from other chromosomes. A simple relationship connects H2 (both in single trait and two-trait analysis) with the expected LOD value, ELOD = -1/2N log(1-H2). Thus, situations could exist that from the inequality H(xy)2(A/a) > or = H(x)2(A/a) a higher resolution is provided by the two-trait analysis as compared to the single-trait analysis, in spite of the increased number of parameters. Employing LOD-score procedure to simulated backcross data, we showed that the resolution power of the QTL mapping model can be elevated if correlation between QTs is taken into account. The method allows us to test numerous biologically important hypotheses concerning manifold effects of genomic segments on the defined trait complex (means, variances and correlations).
14
Xu, S., and W. R. Atchley. "A random model approach to interval mapping of quantitative trait loci." Genetics 141, no. 3 (November 1, 1995): 1189–97. http://dx.doi.org/10.1093/genetics/141.3.1189.
Full textAbstract:
Abstract Mapping quantitative trait loci in outbred populations is important because many populations of organisms are noninbred. Unfortunately, information about the genetic architecture of the trait may not be available in outbred populations. Thus, the allelic effects of genes can not be estimated with ease. In addition, under linkage equilibrium, marker genotypes provide no information about the genotype of a QTL (our terminology for a single quantitative trait locus is QTL while multiple loci are referred to as QTLs). To circumvent this problem, an interval mapping procedure based on a random model approach is described. Under a random model, instead of estimating the effects, segregating variances of QTLs are estimated by a maximum likelihood method. Estimation of the variance component of a QTL depends on the proportion of genes identical-by-descent (IBD) shared by relatives at the locus, which is predicted by the IBD of two markers flanking the QTL. The marker IBD shared by two relatives are inferred from the observed marker genotypes. The procedure offers an advantage over the regression interval mapping in terms of high power and small estimation errors and provides flexibility for large sibships, irregular pedigree relationships and incorporation of common environmental and fixed effects.
15
Scoville, Alison G., Young Wha Lee, John H. Willis, and John K. Kelly. "Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci." Biology Letters 7, no. 6 (June 8, 2011): 896–98. http://dx.doi.org/10.1098/rsbl.2011.0409.
Full textAbstract:
Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V Q , the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.
16
Matthew, Sartie, and M. J. Faville. "A quantitative trait locus analysis of seed production traits in perennial ryegrass (Lolium perenne L.)." NZGA: Research and Practice Series 12 (January 1, 2006): 71–75. http://dx.doi.org/10.33584/rps.12.2006.3039.
Full textAbstract:
A full-sib mapping population (n=188) from a cross between cultivars 'Grasslands Impact' and 'Grasslands Samson' was used to identify quantitative trait loci (QTL) controlling seed yield and component traits in perennial ryegrass. Thirteen traits, including seed yield per plant (SYP) and five seed yield components (number of spikes (SP), spikelets per spike (SS), florets per spikelet (FSP), seed weight (SW) and floret site utilisation (FSU)), seed yield per spike (SYH) and seven other seed yield-associated traits, were phenotypically assessed in a replicated spaced plant field experiment. Interval mapping identified 35 QTL for all traits but one, spanning all linkage groups (LG). Multiple QTL were detected for most traits. QTL for SYP and component traits, as well as some seed yield-associated traits, co-located to the same genomic regions on LG 1, 2 and 6. Markers associated with these regions, in particular, will form the basis for the on-going development of MAS tools for improvement of seed yield and quality in breeding programmes. Further development will require refinement of QTL positions and effects using multiple QTL mapping (MQM), and validation of QTL and associated markers in other genetic backgrounds and environments
17
Corsi, Beatrice, Lia Obinu, Camila M. Zanella, Saverio Cutrupi, Rob Day, Manuel Geyer, Morten Lillemo, et al. "Identification of eight QTL controlling multiple yield components in a German multi-parental wheat population, including Rht24, WAPO-A1, WAPO-B1 and genetic loci on chromosomes 5A and 6A." Theoretical and Applied Genetics 134, no. 5 (March 12, 2021): 1435–54. http://dx.doi.org/10.1007/s00122-021-03781-7.
Full textAbstract:
Abstract Key message Quantitative trait locus (QTL) mapping of 15 yield component traits in a German multi-founder population identified eight QTL each controlling ≥2 phenotypes, including the genetic loci Rht24, WAPO-A1 and WAPO-B1. Abstract Grain yield in wheat (Triticum aestivum L.) is a polygenic trait representing the culmination of many developmental processes and their interactions with the environment. Toward maintaining genetic gains in yield potential, ‘reductionist approaches’ are commonly undertaken by which the genetic control of yield components, that collectively determine yield, are established. Here we use an eight-founder German multi-parental wheat population to investigate the genetic control and phenotypic trade-offs between 15 yield components. Increased grains per ear was significantly positively correlated with the number of fertile spikelets per ear and negatively correlated with the number of infertile spikelets. However, as increased grain number and fertile spikelet number per ear were significantly negatively correlated with thousand grain weight, sink strength limitations were evident. Genetic mapping identified 34 replicated quantitative trait loci (QTL) at two or more test environments, of which 24 resolved into eight loci each controlling two or more traits—termed here ‘multi-trait QTL’ (MT-QTL). These included MT-QTL associated with previously cloned genes controlling semi-dwarf plant stature, and with the genetic locus Reduced height 24 (Rht24) that further modulates plant height. Additionally, MT-QTL controlling spikelet number traits were located to chromosome 7A encompassing the gene WHEAT ORTHOLOG OF APO1 (WAPO-A1), and to its homoeologous location on chromosome 7B containing WAPO-B1. The genetic loci identified in this study, particularly those that potentially control multiple yield components, provide future opportunities for the targeted investigation of their underlying genes, gene networks and phenotypic trade-offs, in order to underpin further genetic gains in yield.
18
Ungerer, Mark C., Solveig S. Halldorsdottir, Michael D. Purugganan, and Trudy F. C. Mackay. "Genotype-Environment Interactions at Quantitative Trait Loci Affecting Inflorescence Development in Arabidopsis thaliana." Genetics 165, no. 1 (September 1, 2003): 353–65. http://dx.doi.org/10.1093/genetics/165.1.353.
Full textAbstract:
Abstract Phenotypic plasticity and genotype-environment interactions (GEI) play a prominent role in plant morphological diversity and in the potential functional capacities of plant life-history traits. The genetic basis of plasticity and GEI, however, is poorly understood in most organisms. In this report, inflorescence development patterns in Arabidopsis thaliana were examined under different, ecologically relevant photoperiod environments for two recombinant inbred mapping populations (Ler × Col and Cvi × Ler) using a combination of quantitative genetics and quantitative trait locus (QTL) mapping. Plasticity and GEI were regularly observed for the majority of 13 inflorescence traits. These observations can be attributable (at least partly) to variable effects of specific QTL. Pooled across traits, 12/44 (27.3%) and 32/62 (51.6%) of QTL exhibited significant QTL × environment interactions in the Ler × Col and Cvi × Ler lines, respectively. These interactions were attributable to changes in magnitude of effect of QTL more often than to changes in rank order (sign) of effect. Multiple QTL × environment interactions (in Cvi × Ler) clustered in two genomic regions on chromosomes 1 and 5, indicating a disproportionate contribution of these regions to the phenotypic patterns observed. High-resolution mapping will be necessary to distinguish between the alternative explanations of pleiotropy and tight linkage among multiple genes.
19
Frary, A., S. Doganlar, A. Frampton, T. Fulton, J. Uhlig, H. Yates, and S. Tanksley. "Fine mapping of quantitative trait loci for improved fruit characteristics from Lycopersicon chmielewskii chromosome 1." Genome 46, no. 2 (April 1, 2003): 235–43. http://dx.doi.org/10.1139/g02-122.
Full textAbstract:
The near-isogenic line (NIL) TA1150 contains a 56-cM introgression from Lycopersicon chmielewskii chromosome 1 and has several interesting phenotypic characteristics including fruit with orange color, high levels of soluble solids, thick pericarp, small stem scars, and good firmness. A set of overlapping recombinant lines (subNILs) was developed and field tested to fine map the quantitative trait loci (QTL) controlling these traits. The results indicated that the solids, pericarp thickness, and firmness QTL are distinct from the color locus. Several of the QTL mapped in this study, including the soluble-solids QTL, probably correspond to QTL mapped in other wild species of tomato. However, analysis of a set of TA523 subNILs containing complementary introgressions from Lycopesicon hirsutum chromosome 1 suggests that this wild species may contain a different locus for improved soluble solids. Thus, it might be possible to combine the L. chmielewskii and L. hirsutum alleles for these loci in a single line with the potential for extremely highly soluble solids. The TA1150 subNIL TA1688 contains the smallest introgression of the solids locus (approximately 19 cM), as well as the pericarp thickness and firmness QTL, with a yield that was equivalent to two of the three control lines. Isolation of recombinant subNILs from TA1688 should break the linkage between orange color and high solids and provide a small introgressed segment for marker-assisted breeding and genetic improvement of processing tomato.Key words: tomato, QTL, soluble solids, Brix, colour.
20
Cockerham, C. Clark, and Zhao-Bang Zeng. "Design III With Marker Loci." Genetics 143, no. 3 (July 1, 1996): 1437–56. http://dx.doi.org/10.1093/genetics/143.3.1437.
Full textAbstract:
Abstract Design III is an experimental design originally proposed by R. E. Comstock and H. F. Robinson for estimating genetic variances and the average degree of dominance for quantitative trait loci (QTL) and has recently been extended for mapping QTL. In this paper, we first extend Comstock and Robinson's analysis of variance to include linkage, two-locus epistasis and the use of F 3 parents. Then we develop the theory and statistical analysis of orthogonal contrasts and contrast × environment interaction for a single marker locus to characterize the effects of QTL. The methods are applied to the maize data of C. W. Stuber. The analyses strongly suggest that there are multiple linked QTL in many chromosomes for several traits examined. QTL effects are largely environment-independent for grain yield, ear height, plant height and ear leaf area and largely environment dependent for days to tassel, grain moisture and ear number. There is significant QTL epistasis. The results are generally in favor of the hypothesis of dominance of favorable genes to explain the observed heterosis in grain yield and other traits, although epistasis could also play an important role and overdominance at individual QTL level can not be ruled out.
21
Sillanpää, Mikko J., and Elja Arjas. "Bayesian Mapping of Multiple Quantitative Trait Loci From Incomplete Outbred Offspring Data." Genetics 151, no. 4 (April 1, 1999): 1605–19. http://dx.doi.org/10.1093/genetics/151.4.1605.
Full textAbstract:
Abstract A general fine-scale Bayesian quantitative trait locus (QTL) mapping method for outcrossing species is presented. It is suitable for an analysis of complete and incomplete data from experimental designs of F2 families or backcrosses. The amount of genotyping of parents and grandparents is optional, as well as the assumption that the QTL alleles in the crossed lines are fixed. Grandparental origin indicators are used, but without forgetting the original genotype or allelic origin information. The method treats the number of QTL in the analyzed chromosome as a random variable and allows some QTL effects from other chromosomes to be taken into account in a composite interval mapping manner. A block-update of ordered genotypes (haplotypes) of the whole family is sampled once in each marker locus during every round of the Markov Chain Monte Carlo algorithm used in the numerical estimation. As a byproduct, the method gives the posterior distributions for linkage phases in the family and therefore it can also be used as a haplotyping algorithm. The Bayesian method is tested and compared with two frequentist methods using simulated data sets, considering two different parental crosses and three different levels of available parental information. The method is implemented as a software package and is freely available under the name Multimapper/outbred at URL http://www.rni.helsinki.fi/~mjs/.
22
HERNÁNDEZ-SÁNCHEZ, J., A. CHATZIPLI, D. BERALDI, J. GRATTEN, J. G. PILKINGTON, and J. M. PEMBERTON. "Mapping quantitative trait loci in a wild population using linkage and linkage disequilibrium analyses." Genetics Research 92, no. 4 (August 2010): 273–81. http://dx.doi.org/10.1017/s0016672310000340.
Full textAbstract:
SummaryHistorical information can be used, in addition to pedigree, traits and genotypes, to map quantitative trait locus (QTL) in general populations via maximum likelihood estimation of variance components. This analysis is known as linkage disequilibrium (LD) and linkage mapping, because it exploits both linkage in families and LD at the population level. The search for QTL in the wild population of Soay sheep on St. Kilda is a proof of principle. We analysed the data from a previous study and confirmed some of the QTLs reported. The most striking result was the confirmation of a QTL affecting birth weight that had been reported using association tests but not when using linkage-based analyses.
23
Lin, Jing-Zhong, and Kermit Ritland. "Quantitative Trait Loci Differentiating the Outbreeding Mimulus guttatus From the Inbreeding M. platycalyx." Genetics 146, no. 3 (July 1, 1997): 1115–21. http://dx.doi.org/10.1093/genetics/146.3.1115.
Full textAbstract:
Theoretical predictions about the evolution of selfing depend on the genetic architecture of loci controlling selfing (monogenic vs. polygenic determination, large vs. small effect of alleles, dominance vs. recessiveness), and studies of such architecture are lacking. We inferred the genetic basis of mating system differences between the outbreeding Mimulus guttatus and the inbreeding M. platycalyx by quantitative trait locus (QTL) mapping using random amplified polymorphic DNA and isozyme markers. One to three QTL were detected for each of five mating system characters, and each QTL explained 7.6–28.6% of the phenotypic variance. Taken together, QTL accounted for up to 38% of the variation in mating system characters, and a large proportion of variation was unaccounted for. Inferred QTL often affected more than one trait, contributing to the genetic correlation between those traits. These results are consistent with the hypothesis that quantitative variation in plant mating system characters is primarily controlled by loci with small effect.
24
Wang, Shibo, Fangjie Xie, and Shizhong Xu. "Estimating genetic variance contributed by a quantitative trait locus: A random model approach." PLOS Computational Biology 18, no. 3 (March 11, 2022): e1009923. http://dx.doi.org/10.1371/journal.pcbi.1009923.
Full textAbstract:
Detecting quantitative trait loci (QTL) and estimating QTL variances (represented by the squared QTL effects) are two main goals of QTL mapping and genome-wide association studies (GWAS). However, there are issues associated with estimated QTL variances and such issues have not attracted much attention from the QTL mapping community. Estimated QTL variances are usually biased upwards due to estimation being associated with significance tests. The phenomenon is called the Beavis effect. However, estimated variances of QTL without significance tests can also be biased upwards, which cannot be explained by the Beavis effect; rather, this bias is due to the fact that QTL variances are often estimated as the squares of the estimated QTL effects. The parameters are the QTL effects and the estimated QTL variances are obtained by squaring the estimated QTL effects. This square transformation failed to incorporate the errors of estimated QTL effects into the transformation. The consequence is biases in estimated QTL variances. To correct the biases, we can either reformulate the QTL model by treating the QTL effect as random and directly estimate the QTL variance (as a variance component) or adjust the bias by taking into account the error of the estimated QTL effect. A moment method of estimation has been proposed to correct the bias. The method has been validated via Monte Carlo simulation studies. The method has been applied to QTL mapping for the 10-week-body-weight trait from an F2 mouse population.
25
De Sanctis, G. T., J. B. Singer, A. Jiao, C. N. Yandava, Y. H. Lee, T. C. Haynes, E. S. Lander, D. R. Beier, and J. M. Drazen. "Quantitative trait locus mapping of airway responsiveness to chromosomes 6 and 7 in inbred mice." American Journal of Physiology-Lung Cellular and Molecular Physiology 277, no. 6 (December 1, 1999): L1118—L1123. http://dx.doi.org/10.1152/ajplung.1999.277.6.l1118.
Full textAbstract:
Quantitative trait locus (QTL) mapping was used to identify chromosomal regions contributing to airway hyperresponsiveness in mice. Airway responsiveness to methacholine was measured in A/J and C3H/HeJ parental strains as well as in progeny derived from crosses between these strains. QTL mapping of backcross [(A/J × C3H/HeJ) × C3H/HeJ] progeny ( n = 137–227 informative mice for markers tested) revealed two significant linkages to loci on chromosomes 6 and 7. The QTL on chromosome 6 confirms the previous report by others of a linkage in this region in the same genetic backgrounds; the second QTL, on chromosome 7, represents a novel locus. In addition, we obtained suggestive evidence for linkage (logarithm of odds ratio = 1.7) on chromosome 17, which lies in the same region previously identified in a cross between A/J and C57BL/6J mice. Airway responsiveness in a cross between A/J and C3H/HeJ mice is under the control of at least two major genetic loci, with evidence for a third locus that has been previously implicated in an A/J and C57BL/6J cross; this indicates that multiple genetic factors control the expression of this phenotype.
26
Prothro, Jason, Katherine Sandlin, Rattandeep Gill, Eleni Bachlava, Victoria White, Steven J. Knapp, and Cecilia McGregor. "Mapping of the Egusi Seed Trait Locus (eg) and Quantitative Trait Loci Associated with Seed Oil Percentage in Watermelon." Journal of the American Society for Horticultural Science 137, no. 5 (September 2012): 311–15. http://dx.doi.org/10.21273/jashs.137.5.311.
Full textAbstract:
The egusi watermelon (Citrullus lanatus) is popular in West Africa for its oil and protein-rich seed, which is consumed in soups and stews. The egusi phenotypic trait is controlled by a single recessive gene (eg) and is characterized by large seed size and fleshy, thick pericarp. An F2 mapping population was derived from Strain II (PI 279461) of the Japanese cultivar Yamato-cream with normal seed type and low seed oil percentage (SOP = 25.2%) and an egusi type from Nigeria [Egusi (PI 560023)] with high SOP (40.6%). Genetic analysis confirmed that the egusi seed trait is controlled by a single recessive gene (eg) and the location of the gene was mapped to 57.8 cM on linkage group (LG) 2, between markers NW0248325 and NW0250248. Four main quantitative trait loci (M-QTL) were identified for SOP in the population with the eg locus contributing 84% of the explained phenotypic variation (R2). A significant epistatic interaction (E-QTL) was identified between, the eg locus and an M-QTL on LG 9B. The present study reports the location of the eg locus responsible for the egusi seed trait in watermelon on LG 2 as well as M-QTL and E-QTL associated with SOP.
27
Uimari, Pekka, and Ina Hoeschele. "Mapping-Linked Quantitative Trait Loci Using Bayesian Analysis and Markov Chain Monte Carlo Algorithms." Genetics 146, no. 2 (June 1, 1997): 735–43. http://dx.doi.org/10.1093/genetics/146.2.735.
Full textAbstract:
A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL and no additional or an unlinked QTL.
28
DENG, Z. Y., W. J. LI, F. CHEN, W. Q. FANG, G. F. CHEN, C. L. SUN, Y. X. ZHANG, S. Y. WANG, and J. C. TIAN. "Genetic dissection of flour whiteness by unconditional and conditional quantitative trait locus mapping in wheat." Journal of Agricultural Science 155, no. 4 (September 9, 2016): 544–55. http://dx.doi.org/10.1017/s0021859616000563.
Full textAbstract:
SUMMARYFlour whiteness (FW) is an important factor in assessing flour quality and determining the end product quality. It is an integrated sensory indicator reflecting flour colour and is negatively correlated with protein content. In order to dissect the genetic relationship between FW and its five related traits at the quantitative trait locus (QTL)/gene level, a recombinant inbred line population was evaluated under three environments. Quantitative trait loci for FW were analysed by unconditional and conditional QTL mapping. Four unconditional additive QTLs and 16 conditional additive QTLs were detected across the three environments. Of these QTLs, only one major additive QTL (Qfw1D1-1) was consistently identified using both unconditional and conditional QTL analysis. This QTL was independent of flour colour a* (a function of red-green with a positive a* for redness and negative for greenness) and b* (a green-blue value with positive value for yellowness and negative for blueness) and was only slightly affected by flour protein content. A minor additive QTL (Qfw4A-4) was also detected using these two QTL mapping methods, being independent of flour colour a* and b*. Five unconditional and ten conditional epistatic minor QTLs were detected, from which only one pair (Qfw3A-10/Qfw6B-6) was identified by both unconditional and conditional QTL mapping, also independent of flour colour a* and b*. The major QTL (Qfw1D1-1) identified in the current study for the first time can be used for improving wheat FW in marker-assisted breeding.
29
Tsujita, Yasuyuki, Naoharu Iwai, Shinji Tamaki, Yasuyuki Nakamura, Masato Nishimura, and Masahiko Kinoshita. "Genetic mapping of quantitative trait loci influencing left ventricular mass in rats." American Journal of Physiology-Heart and Circulatory Physiology 279, no. 5 (November 1, 2000): H2062—H2067. http://dx.doi.org/10.1152/ajpheart.2000.279.5.h2062.
Full textAbstract:
High blood pressure is the leading cause of left ventricular hypertrophy (LVH); however, not all hypertensive patients develop LVH. Genetic factors are important in the development of LVH. With the use of F2 male rats from spontaneously hypertensive rats and Lewis rats, we performed a study to identify the quantitative trait loci (QTL) that influence left ventricular mass (LVM). Mean arterial pressure (MAP) was measured by the direct intra-arterial method in conscious animals, and LVM was determined at 24 wk of age. QTL analysis was done using 160 microsatellite markers for a genome-wide scan. Two loci that influenced body weight-adjusted LVM with logarithm of the odds scores >3.4 were found. One locus on chromosome 17 influenced LVM independently of MAP. Another locus on chromosome 7 influenced LVM and MAP. These findings indicate not only the existence of a gene on chromosome 7 that influences LVM in a manner dependent on blood pressure but also the existence of a gene on chromosome 17 that influences LVM independently of blood pressure.
30
Nakamichi, Reiichiro, Yasuo Ukai, and Hirohisa Kishino. "Detection of Closely Linked Multiple Quantitative Trait Loci Using a Genetic Algorithm." Genetics 158, no. 1 (May 1, 2001): 463–75. http://dx.doi.org/10.1093/genetics/158.1.463.
Full textAbstract:
AbstractThe existence of a quantitative trait locus (QTL) is usually tested using the likelihood of the quantitative trait on the basis of phenotypic character data plus the recombination fraction between QTL and flanking markers. When doing this, the likelihood is calculated for all possible locations on the linkage map. When multiple QTL are suspected close by, it is impractical to calculate the likelihood for all possible combinations of numbers and locations of QTL. Here, we propose a genetic algorithm (GA) for the heuristic solution of this problem. GA can globally search the optimum by improving the “genotype” with alterations called “recombination” and “mutation.” The “genotype” of our GA is the number and location of QTL. The “fitness” is a function based on the likelihood plus Akaike’s information criterion (AIC), which helps avoid false-positive QTL. A simulation study comparing the new method with existing QTL mapping packages shows the advantage of the new GA. The GA reliably distinguishes multiple QTL located in a single marker interval.
31
Yuan, Lei, Licheng Zhang, Xiao Wei, Ruihua Wang, Nannan Li, Gaili Chen, Fengfeng Fan, Shaoying Huang, Jianxiong Li, and Shaoqing Li. "Quantitative Trait Locus Mapping of Salt Tolerance in Wild Rice Oryza longistaminata." International Journal of Molecular Sciences 23, no. 4 (February 21, 2022): 2379. http://dx.doi.org/10.3390/ijms23042379.
Full textAbstract:
Salt stress is one of the most severe adverse environments in rice production; increasing salinization is seriously endangering rice production around the world. In this study, a rice backcross inbred line (BIL) population derived from the cross of 9311 and wild rice Oryza longistaminata was employed to identify the favorable genetic loci of O. longistaminata for salt tolerance. A total of 27 quantitative trait loci (QTLs) related to salt tolerance were identified in 140 rice BILs, and 17 QTLs formed seven QTL clusters on different chromosomes, of which 18 QTLs were derived from O. longistaminata, and a QTL for salt injury score (SIS), water content of seedlings (WCS) under salt treatment, and relative water content of seedlings (RWCS) was repeatedly detected and colocalized at the same site on chromosome 2, and a cytochrome P450 86B1 (MH02t0466900) was suggested as the potential candidate gene responsible for the salt tolerance based on sequence and expression analysis. These findings laid the foundation for further improving rice salt tolerance through molecular breeding in the future.
32
Cumagun, Christian Joseph R., Robert L. Bowden, James E. Jurgenson, John F. Leslie, and Thomas Miedaner. "Genetic Mapping of Pathogenicity and Aggressiveness of Gibberella zeae (Fusarium graminearum) Toward Wheat." Phytopathology® 94, no. 5 (May 2004): 520–26. http://dx.doi.org/10.1094/phyto.2004.94.5.520.
Full textAbstract:
Gibberella zeae is the major fungal pathogen of Fusarium head blight of wheat and produces several mycotoxins that are harmful to humans and domesticated animals. We identified loci associated with pathogenicity and aggressiveness on an amplified fragment length polymorphism based genetic map of G. zeae in a cross between a lineage 6 nivalenol producer from Japan and a lineage 7 deoxynivalenol producer from Kansas. Ninety-nine progeny and the parents were tested in the greenhouse for 2 years. Progeny segregated qualitatively (61:38) for pathogenicity:nonpathogenicity, respectively. The trait maps to linkage group IV, which is adjacent to loci that affect colony pigmentation, perithecium production, and trichothecene toxin amount. Among the 61 pathogenic progeny, the amount of disease induced (aggressiveness) varied quantitatively. Two reproducible quantitative trait loci (QTL) for aggressiveness were detected on linkage group I using simple interval analysis. A QTL linked to the TRI5 locus (trichodiene synthase in the trichothecene pathway gene cluster) explained 51% of the variation observed, and a second QTL that was 50 centimorgans away explained 29% of the phenotypic variation. TRI5 is tightly linked to the locus controlling trichothecene toxin type. The two QTLs, however, were likely part of the same QTL using composite interval analysis. Progeny that produced deoxynivalenol were, on average, approximately twice as aggressive as those that produced nivalenol. No transgressive segregation for aggressiveness was detected. The rather simple inheritance of both traits in this interlineage cross suggests that relatively few loci for pathogenicity or aggressiveness differ between lineage 6 and 7.
33
Groover, A., M. Devey, T. Fiddler, J. Lee, R. Megraw, T. Mitchel-Olds, B. Sherman, S. Vujcic, C. Williams, and D. Neale. "Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine." Genetics 138, no. 4 (December 1, 1994): 1293–300. http://dx.doi.org/10.1093/genetics/138.4.1293.
Full textAbstract:
Abstract We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.). QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (> 2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among alleles at QTL (deviation from additive gene action). Restriction fragment length polymorphism (RFLP) marker genotypes and wood specific gravity phenotypes were determined for 177 progeny. Two RFLP linkage maps were constructed, representing maternal and paternal parent gamete segregations as inferred from diploid progeny RFLP genotypes. RFLP loci segregating for multiple alleles were vital for aligning the two maps. Each RFLP locus was assayed for cosegregation with WSG QTL using analysis of variance (ANOVA). Five regions of the genome contained one or more RFLP loci showing differences in mean WSG at or below the P = 0.05 level for progeny as grouped by RFLP genotype. One region contained a marker locus (S6a) whose QTL-associated effects were highly significant (P > 0.0002). Marker S6a segregated for multiple alleles, a prerequisite for determining the number of alleles segregating at the linked QTL and analyzing the interactions among QTL alleles. The QTL associated with marker S6a appeared to be segregating for multiple alleles which interacted with each other and with environments. No evidence for digenic epistasis was found among the five QTL.
34
Molnar, Stephen J., Martin Charette, and Elroy R. Cober. "Mapping quantitative trait loci for water uptake in a recombinant inbred line population of natto soybean." Canadian Journal of Plant Science 92, no. 2 (March 2012): 257–66. http://dx.doi.org/10.4141/cjps2011-122.
Full textAbstract:
Molnar, S. J., Charette, M. and Cober, E. R. 2012. Mapping quantitative trait loci for water uptake in a recombinant inbred line population of natto soybean. Can. J. Plant Sci. 92: 257–266. Small-seeded natto soybeans are soaked in the first step of producing natto. Water uptake traits play a role in the quality of the end product. The objectives of the current study were to use a recombinant inbred line (RIL) mapping population contrasting for water uptake traits to develop its molecular marker recombination map, and to use quantitative trait locus (QTL) analysis to characterize the genetics of water uptake and identify molecular markers for marker assisted breeding. A RIL population (AC Colibri×OT91-3) was tested for multiple years at Ottawa, Ontario, Canada. Two water uptake parameters (a16 and b) were estimated by fitting a curve for an exponential rise to a maximum. Both parameters were affected by year, genotype and the interaction effects. Seed yield, seed composition and agronomic traits were also measured. Simple sequence repeat (SSR) markers were used to genotype the population and develop a recombination map. QTL analysis identified two QTL for a16 on molecular linkage groups (MLG) D2 and E and three QTL for b on A2, J and M. Three of these QTL map to similar intervals as known QTL for seed weight, seed yield and seed fill in diverse populations. The fourth may correspond with a known QTL for water absorbability during germination and the fifth maps at or near known flowering time and maturity QTL.
35
Bernal, Eduardo, Debora Liabeuf, and David M. Francis. "Evaluating Quantitative Trait Locus Resistance in Tomato to Multiple Xanthomonas spp." Plant Disease 104, no. 2 (February 2020): 423–29. http://dx.doi.org/10.1094/pdis-03-19-0669-re.
Full textAbstract:
Bacterial spot of tomato is a foliar disease caused by four Xanthomonas species. Identifying genetic resistance in wild tomatoes and subsequent breeding of varieties has been a strategy to reduce the loss from this disease because control using pesticides has been ineffective. Three independent sources of resistance have been identified with quantitative trait loci (QTL) mapping to the centromeric region on chromosome 11. These sources are derived from Hawaii 7998 (QTL-11A), PI 114490 (QTL-11B), and LA2533 (QTL-11C). To determine which QTL introgression from chromosome 11 provides the greatest resistance to multiple species, we developed near-isogenic lines (NILs) using marker-assisted backcrossing. In parallel, we developed an NIL that contains Rx-4/Xv3, which provides major gene resistance to Xanthomonas perforans. Additionally, we combined Rx-4/Xv3 resistance with QTL-11A. These sources of resistance were independently introduced into the susceptible parent, OH88119. During a 3-year period from 2016 to 2018, we evaluated backcross-derived families and NILs from each source in independent field trials inoculated with X. perforans, X. euvesicatoria, or X. gardneri. Our results suggest that both QTL-11C and QTL-11A combined with Rx-4/Xv3 provide effective genetic resistance against multiple Xanthomonas species. In addition, we provide evidence for additive to dominant genetic action for the QTL introgressions.
36
Zheng, Zhanye, Dandan Huang, Jianhua Wang, Ke Zhao, Yao Zhou, Zhenyang Guo, Sinan Zhai, et al. "QTLbase: an integrative resource for quantitative trait loci across multiple human molecular phenotypes." Nucleic Acids Research 48, no. D1 (October 10, 2019): D983—D991. http://dx.doi.org/10.1093/nar/gkz888.
Full textAbstract:
Abstract Recent advances in genome sequencing and functional genomic profiling have promoted many large-scale quantitative trait locus (QTL) studies, which connect genotypes with tissue/cell type-specific cellular functions from transcriptional to post-translational level. However, no comprehensive resource can perform QTL lookup across multiple molecular phenotypes and investigate the potential cascade effect of functional variants. We developed a versatile resource, named QTLbase, for interpreting the possible molecular functions of genetic variants, as well as their tissue/cell-type specificity. Overall, QTLbase has five key functions: (i) curating and compiling genome-wide QTL summary statistics for 13 human molecular traits from 233 independent studies; (ii) mapping QTL-relevant tissue/cell types to 78 unified terms according to a standard anatomogram; (iii) normalizing variant and trait information uniformly, yielding >170 million significant QTLs; (iv) providing a rich web client that enables phenome- and tissue-wise visualization; and (v) integrating the most comprehensive genomic features and functional predictions to annotate the potential QTL mechanisms. QTLbase provides a one-stop shop for QTL retrieval and comparison across multiple tissues and multiple layers of molecular complexity, and will greatly help researchers interrogate the biological mechanism of causal variants and guide the direction of functional validation. QTLbase is freely available at http://mulinlab.org/qtlbase.
37
Foulongne-Oriol, Marie, Anne Rodier, and Jean-Michel Savoie. "Relationship between Yield Components and Partial Resistance to Lecanicillium fungicola in the Button Mushroom, Agaricus bisporus, Assessed by Quantitative Trait Locus Mapping." Applied and Environmental Microbiology 78, no. 7 (January 13, 2012): 2435–42. http://dx.doi.org/10.1128/aem.07554-11.
Full textAbstract:
ABSTRACTDry bubble, caused byLecanicillium fungicola, is one of the most detrimental diseases affecting button mushroom cultivation. In a previous study, we demonstrated that breeding for resistance to this pathogen is quite challenging due to its quantitative inheritance. A second-generation hybrid progeny derived from an intervarietal cross between a wild strain and a commercial cultivar was characterized forL. fungicolaresistance under artificial inoculation in three independent experiments. Analysis of quantitative trait loci (QTL) was used to determine the locations, numbers, and effects of genomic regions associated with dry-bubble resistance. Four traits related to resistance were analyzed. Two to four QTL were detected per trait, depending on the experiment. Two genomic regions, on linkage group X (LGX) and LGVIII, were consistently detected in the three experiments. The genomic region on LGX was detected for three of the four variables studied. The total phenotypic variance accounted for by all QTL ranged from 19.3% to 42.1% over all traits in all experiments. For most of the QTL, the favorable allele for resistance came from the wild parent, but for some QTL, the allele that contributed to a higher level of resistance was carried by the cultivar. Comparative mapping with QTL for yield-related traits revealed five colocations between resistance and yield component loci, suggesting that the resistance results from both genetic factors and fitness expression. The consequences for mushroom breeding programs are discussed.
38
Lightfoot, J. Timothy, Michael J. Turner, Amy Kleinfehn Knab, Anne E. Jedlicka, Tomohiro Oshimura, Jacqui Marzec, Wesley Gladwell, Larry J. Leamy, and Steven R. Kleeberger. "Quantitative trait loci associated with maximal exercise endurance in mice." Journal of Applied Physiology 103, no. 1 (July 2007): 105–10. http://dx.doi.org/10.1152/japplphysiol.01328.2006.
Full textAbstract:
The role of genetics in the determination of maximal exercise endurance is unclear. Six- to nine-week-old F2 mice ( n = 99; 60 female, 39 male), derived from an intercross of two inbred strains that had previously been phenotyped as having high maximal exercise endurance (Balb/cJ) and low maximal exercise endurance (DBA/2J), were treadmill tested to estimate exercise endurance. Selective genotyping of the F2 cohort ( n = 12 high exercise endurance; n = 12 low exercise endurance) identified a significant quantitative trait locus (QTL) on chromosome X (53.7 cM, DXMit121) in the entire cohort and a suggestive QTL on chromosome 8 (36.1 cM, D8Mit359) in the female mice. Fine mapping with the entire F2 cohort and additional informative markers confirmed and narrowed the QTLs. The chromosome 8 QTL ( EE8 F) is homologous with two suggestive human QTLs and one significant rat QTL previously linked with exercise endurance. No effect of sex ( P = 0.33) or body weight ( P = 0.79) on exercise endurance was found in the F2 cohort. These data indicate that genetic factors in distinct chromosomal regions may affect maximal exercise endurance in the inbred mouse. Whereas multiple genes are located in the identified QTL that could functionally affect exercise endurance, this study serves as a foundation for further investigations delineating the identity of genetic factors influencing maximum exercise endurance.
39
He, Xinyao, Susanne Dreisigacker, Carolina Sansaloni, Etienne Duveiller, Ravi P. Singh, and Pawan K. Singh. "Quantitative Trait Loci Mapping for Spot Blotch Resistance in Two Biparental Mapping Populations of Bread Wheat." Phytopathology® 110, no. 12 (December 2020): 1980–87. http://dx.doi.org/10.1094/phyto-05-20-0197-r.
Full textAbstract:
Spot blotch (SB), caused by Bipolaris sorokiniana, is a major fungal disease of wheat in South Asia and South America. Two biparental mapping populations with 232 F2:7 progenies each were generated, with CIMMYT breeding lines CASCABEL and KATH as resistant parents and CIANO T79 as the common susceptible parent. The two populations were evaluated for field SB resistance in CIMMYT’s Agua Fria station for three consecutive cropping seasons, with artificial inoculation. Genotyping was done with the DArTseq platform and approximately 1,500 high quality and nonredundant markers were used for quantitative trait loci (QTL) mapping. In both populations, a major QTL was found on chromosome 5A in the Vrn-A1 region, explaining phenotypic variations of 13.5 to 25.9%, which turned up to be less- or nonsignificant when days to heading and plant height were used as covariates in the analysis, implying a disease escape mechanism. Another major QTL was located on chromosome 5B in CASCABEL, accounting for 8.9 to 21.4% of phenotypic variation. Minor QTL were found on 4A and 4B in CASCABEL; 1B, 4B, and 4D in KATH; and 1B, 2B, and 4B in CIANO T79. Through an analysis of QTL projection onto the IWGSC Chinese Spring reference genome, the 5B QTL in CASCABEL was mapped in the Sb2 region, delimited by the single nucleotide polymorphism marker wsnp_Ku_c50354_55979952 and the simple sequence repeat marker gwm213, with a physical distance of about 14 Mb to the Tsn1 locus.
40
Ricciardi, M., E. Tocho, M. S. Tacaliti, A. Vasicek, D. O. Giménez, A. Paglione, J. Simmonds, J. W. Snape, M. Cakir, and A. M. Castro. "Mapping quantitative trait loci for resistance against Russian wheat aphid (Diuraphis noxia) in wheat (Triticum aestivum L.)." Crop and Pasture Science 61, no. 12 (2010): 970. http://dx.doi.org/10.1071/cp10188.
Full textAbstract:
Diuraphis noxia (Russian wheat aphid, RWA), one of the most aggressive pests of wheat, has evolved several biotypes with virulence matching known Dn resistance genes. This paper was aimed at determining the location of plant-defence genes triggered by RWA in a set of doubled haploid (DH) lines obtained from the cross of winter wheat varieties ‘Spark’ and ‘Rialto’. Both parental lines, 110 DH and CItr2401 (a RWA-resistant line) were screened for antixenosis, tolerance and antibiotic mechanisms of resistance with a population of RWA collected in Argentina. Antixenosis was not significantly linked to any marker locus. Tolerance traits showed significant associations with several chromosomes. Quantitative trait loci (QTL) for the foliar area developed during infestation was significantly associated with marker loci Xpsp3103 on 4DS, and Xgdm3 on 5DS. QTL for chlorophyll content in the infested plants were significantly associated with the marker loci Xgwm533 on 3BS and Xpsp3094 on 7AL, and a QTL for the number of expanded leaves was associated with the marker loci Xwmc264 on 3AS and XwPt8836 on 4DS. QTL for most of the tolerance traits were significantly associated with the same chromosome intervals on chromosomes 4DS and 5DS. The 4DS QTL were linked to or had a pleiotropic effect on Rht-D1. Most of the antibiosis traits were significantly associated with the same marker loci on chromosomes 4A (XwPt7405), 1B (XwPt9032) and 5B (Xbarc109 and Xbarc74). Several novel genes conferring tolerance and antibiosis to RWA were identified and these could be transferred into wheat cultivars to enlarge the genetic base of defence against this aphid pest. These new genes can be designated as QDn.unlp genes, following the rules for gene nomenclature in wheat.
41
Schäfer-Pregl, R., F. Salamini, and C. Gebhardt. "Models for mapping quantitative trait loci (QTL) in progeny of non-inbred parents and their behaviour in presence of distorted segregation ratios." Genetical Research 67, no. 1 (February 1996): 43–54. http://dx.doi.org/10.1017/s0016672300033462.
Full textAbstract:
SummaryIn plants, models for mapping quantitative trait loci (QTL) based on flanking markers have been mainly developed for progenies of inbred lines. We propose twoflanking marker models for QTL mapping in F1 progenies of non-inbred parents. The first is based on the segregation of four different scorable alleles at a marker locus (the four-allele model) and the second (the commonallele model) on one scorable allele per marker locus segregating in both parents. These models are suitable for the majority of the allelic configurations which may occur in crosses between heterozygous parents. For both cases, when four scorable or one common-allele per marker locus segregate, additional algorithms were developed to estimate the recombination frequency between two marker loci. Tests carried out with simulated populations of various sizes indicate that the models provide a good estimate of QTL genotypic means and of recombination frequencies between flanking markers and between the marker loci and the QTL.The estimates of QTL genotypic means have a higher precision than the estimates of recombination frequencies. The four-allele model shows a higher ability to detect QTLs than the common-allele model. If segregation ratios are distorted, the power of both models and the precision of the estimates of recombination frequencies are reduced, whereas the accuracy of estimates of QTL genotype means is not affected by distorted segregation ratios. The power of the common-allele model is substantially reduced if QTL genotypic means depend on additive allelic interactions, whereas the four-allele model is less affected by the non-additive behaviour of QTL alleles.
42
LUO, Z. W., and L. MA. "An improved formulation of marker heterozygosity in recurrent selection and backcross schemes." Genetical Research 83, no. 1 (February 2004): 49–53. http://dx.doi.org/10.1017/s0016672303006517.
Full textAbstract:
This report presents a theoretical formulation for predicting heterozygosity of a putative marker locus linked to two quantitative trait loci (QTL) in a recurrent selection and backcross (RSB) scheme. Since the heterozygosity at any given marker locus maintained in such a breeding programme reflects its map location relative to QTL, the present study develops the theoretical analysis of the QTL mapping method that recently appeared in the literature. The formulae take into account selection, recombination and finite population size during the multiple-generation breeding scheme. The single-marker and two-QTL model was compared numerically with the model involving two linked marker loci and two QTL. Without recombination interference, the two models predict the same expected heterozygosity at the linked marker loci, indicating that the model is valid for predicting marker heterozygosity maintained at any loci in an RSB breeding scheme. The formulation is demonstrated numerically for several RSB schemes and its implications in developing a likelihood-based statistical framework for modeling the RSB experiments are discussed.
43
Mangin, B., P. Thoquet, J. Olivier, and N. H. Grimsley. "Temporal and Multiple Quantitative Trait Loci Analyses of Resistance to Bacterial Wilt in Tomato Permit the Resolution of Linked Loci." Genetics 151, no. 3 (March 1, 1999): 1165–72. http://dx.doi.org/10.1093/genetics/151.3.1165.
Full textAbstract:
Abstract Ralstonia solanacearum is a soil-borne bacterium that causes the serious disease known as bacterial wilt in many plant species. In tomato, several QTL controlling resistance have been found, but in different studies, markers spanning a large region of chromosome 6 showed strong association with the resistance. By using two different approaches to analyze the data from a field test F3 population, we show that at least two separate loci ∼30 cM apart on this chromosome are most likely involved in the resistance. First, a temporal analysis of the progression of symptoms reveals a distal locus early in the development of the disease. As the disease progresses, the maximum LOD peak observed shifts toward the proximal end of the chromosome, obscuring the distal locus. Second, although classical interval mapping could only detect the presence of one locus, a statistical “two-QTL model” test, specifically adapted for the resolution of linked QTL, strongly supported the hypothesis for the presence of two loci. These results are discussed in the context of current molecular knowledge about disease resistance genes on chromosome 6 and observations made by tomato breeders during the production of bacterial wilt-resistant varieties.
44
Sillanpää, Mikko J., and Elja Arjas. "Bayesian Mapping of Multiple Quantitative Trait Loci From Incomplete Inbred Line Cross Data." Genetics 148, no. 3 (March 1, 1998): 1373–88. http://dx.doi.org/10.1093/genetics/148.3.1373.
Full textAbstract:
Abstract A novel fine structure mapping method for quantitative traits is presented. It is based on Bayesian modeling and inference, treating the number of quantitative trait loci (QTLs) as an unobserved random variable and using ideas similar to composite interval mapping to account for the effects of QTLs in other chromosomes. The method is introduced for inbred lines and it can be applied also in situations involving frequent missing genotypes. We propose that two new probabilistic measures be used to summarize the results from the statistical analysis: (1) the (posterior) QTL-intensity, for estimating the number of QTLs in a chromosome and for localizing them into some particular chromosomal regions, and (2) the location wise (posterior) distributions of the phenotypic effects of the QTLs. Both these measures will be viewed as functions of the putative QTL locus, over the marker range in the linkage group. The method is tested and compared with standard interval and composite interval mapping techniques by using simulated backcross progeny data. It is implemented as a software package. Its initial version is freely available for research purposes under the name Multimapper at URL http://www.rni.helsinki.fi/~mjs.
45
Pitman, Wendy A., Ron Korstanje, Gary A. Churchill, Edwige Nicodeme, John J. Albers, Marian C. Cheung, Megan A. Staton, Stephen S. Sampson, Stephen Harris, and Beverly Paigen. "Quantitative trait locus mapping of genes that regulate HDL cholesterol in SM/J and NZB/B1NJ inbred mice." Physiological Genomics 9, no. 2 (May 10, 2002): 93–102. http://dx.doi.org/10.1152/physiolgenomics.00107.2001.
Full textAbstract:
To investigate the quantitative trait loci (QTL) regulating plasma cholesterol, the female progeny of an (SM×NZB/ B1NJ)×NZB/B1NJ backcross were fed an atherogenic diet. After 18 wk, plasma total cholesterol and high-density lipoprotein cholesterol (HDL-C) was measured. HDL-C concentrations were greater in NZB than in SM mice. For standard chow-fed mice, QTL were found near D5Mit370 and D18Mit34. For mice fed an atherogenic diet, a QTL was found near D5Mit239. The QTL for chow-fed and atherogenic-fed mice on chromosome 5 seem to be two different loci. We used a multitrait analysis to rule out pleiotropy in favor of a two-QTL hypothesis. Furthermore, the HDL-C in these strains was induced by the high-fat diet. For inducible HDL-C, one significant locus was found near D15Mit39. The gene for an HDL receptor, Srb1, maps close to the HDL-C QTL at D5Mit370, but the concentrations of Srb1 mRNA and SR-B1 protein and the gene sequence of NZB/B1NJ and SM/J did not support Srb1 as a candidate gene. With these QTL, we have identified chromosomal regions that affect lipoprotein profiles in these strains.
46
LIU, XIAOJUN, FIONA OLIVER, STEVE D. M. BROWN, PAUL DENNY, and PETER D. KEIGHTLEY. "High-resolution quantitative trait locus mapping for body weight in mice by recombinant progeny testing." Genetical Research 77, no. 2 (April 2001): 191–97. http://dx.doi.org/10.1017/s0016672301004943.
Full textAbstract:
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.
47
Lu, Lu, Hui Liu, Yu Wu, and Guijun Yan. "Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.)." Plants 11, no. 6 (March 9, 2022): 729. http://dx.doi.org/10.3390/plants11060729.
Full textAbstract:
Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R2 were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.
48
Knott, Sara A., Lena Marklund, Chris S. Haley, Kjell Andersson, William Davies, Hans Ellegren, Merete Fredholm, et al. "Multiple Marker Mapping of Quantitative Trait Loci in a Cross Between Outbred Wild Boar and Large White Pigs." Genetics 149, no. 2 (June 1, 1998): 1069–80. http://dx.doi.org/10.1093/genetics/149.2.1069.
Full textAbstract:
Abstract A quantitative trait locus (QTL) analysis of growth and fatness data from a three generation pig experiment is presented. The population of 199 F2 animals was derived from a cross between wild boar and Large White pigs. Animals were typed for 240 markers spanning 23 Morgans of 18 autosomes and the X chromosome. A series of analyses are presented within a least squares framework. First, these identify chromosomes containing loci controlling trait variation and subsequently attempt to map QTLs to locations within chromosomes. This population gives evidence for a large QTL affecting back fat and another for abdominal fat segregating on chromosome 4. The best locations for these QTLs are within 4 cM of each other and, hence, this is likely to be a single QTL affecting both traits. The allele inherited from the wild boar causes an increase in fat deposition. A QTL for intestinal length was also located in the same region on chromosome 4 and could be the same QTL with pleiotropic effects. Significant effects, owing to multiple QTLs, for intestinal length were identified on chromosomes 3 and 5. A single QTL affecting growth rate to 30 kg was located on chromosome 13 such that the Large White allele increased early growth rate, another QTL on chromosome 10 affected growth rate from 30 to 70 kg and another on chromosome 4 affected growth rate to 70 kg.
49
Severson, D. W., V. Thathy, A. Mori, Y. Zhang, and B. M. Christensen. "Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti." Genetics 139, no. 4 (April 1, 1995): 1711–17. http://dx.doi.org/10.1093/genetics/139.4.1711.
Full textAbstract:
Abstract Susceptibility of the mosquito Aedes aegypti to the malarial parasite Plasmodium gallinaceum was investigated as a quantitative trait using restriction fragment length polymorphisms (RFLP). Two F2 populations of mosquitoes were independently prepared from pairwise matings between a highly susceptible and a refractory strain of A. aegypti. RFLP were tested for association with oocyst development on the mosquito midgut. Two putative quantitative trait loci (QTL) were identified that significantly affect susceptibility. One QTL, pgs[2,LF98], is located on chromosome 2 and accounted for 65 and 49% of the observed phenotypic variance in the two populations, respectively. A second QTL, pgs[3,MalI], is located on chromosome 3 and accounted for 14 and 10% of the observed phenotypic variance in the two populations, respectively. Both QTL exhibit a partial dominance effect on susceptibility, wherein the dominance effect is derived from the refractory parent. No indication of epistasis between these QTL was detected. Evidence suggests that either a tightly linked cluster of independent genes or a single locus affecting susceptibility to various mosquito-borne parasites and pathogens has evolved near the LF98 locus; in addition to P. gallinaceum susceptibility, this general genome region has previously been implicated in susceptibility to the filarial nematode Brugia malayi and the yellow fever virus.
50
TAYLOR, SANDRA L., and KATHERINE S. POLLARD. "Composite interval mapping to identify quantitative trait loci for point-mass mixture phenotypes." Genetics Research 92, no. 1 (February 2010): 39–53. http://dx.doi.org/10.1017/s0016672310000042.
Full textAbstract:
SummaryIncreasingly researchers are conducting quantitative trait locus (QTL) mapping in metabolomics and proteomics studies. These data often are distributed as a point-mass mixture, consisting of a spike at zero in combination with continuous non-negative measurements. Composite interval mapping (CIM) is a common method used to map QTL that has been developed only for normally distributed or binary data. Here we propose a two-part CIM method for identifying QTLs when the phenotype is distributed as a point-mass mixture. We compare our new method with existing normal and binary CIM methods through an analysis of metabolomics data from Arabidopsis thaliana. We then conduct a simulation study to further understand the power and error rate of our two-part CIM method relative to normal and binary CIM methods. Our results show that the two-part CIM has greater power and a lower false positive rate than the other methods when a continuous phenotype is measured with many zero observations.