Showing papers on "Quantitative trait locus published in 1987"

Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Abstract: Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17-20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800-1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.

Molecular marker-facilitated investigations of quantitative trait loci in maize. II. Factors influencing yield and its component traits

Abstract: Because traits such as grain yield are polygenically inherited and strongly influenced by environment, determination of genotypic values from phenotypic expression is not precise and improvement strategies are frequently based on low heritabilities. Increased knowledge of the genetic factors involved in the expression of yield should enhance the improvement of this trait. The objectives of this study were to identify and locate genetic factors (i.e., quantitative trait loci, QTL's) associated with grain yield and 24 yield-related traits in two F, populations of maize (Zea mays L.) using isozyme marker loci. (The populations were generated by selfing the F, hybrids CO159 X Tx303 and T232 X CM37.) In addition, assessments of the types and magnitudes of gene effects expressed by these QTL's were made. About two-thirds of the associations among 17 to 20 marker loci and the 25 quantitative traits were significant with a large proportion of these at P < 0.001. Proportions of variation accounted for by genetic factors associated with individual marker loci varied from less than 1% to more than 11%. Although individual marker loci accounted for relatively small proportions of the phenotypic variation for these yield-related traits, differences between mean phenotypic values of the two homozygous classes at certain loci were occasionally more than 16% of the population mean. Also, different genomic regions contributed to yield through different subsets of the yield-related traits. Predominant types of gene action varied among loci and among the 25 quantitative traits. For plant grain yield, top ear grain weight, and ear length, the gene action was primarily dominant or overdominant. However, mainly additive gene action was implicated for ear number, kernel row number, and second ear grain weight. Results from these studies should prove to be useful for manipulating QTL's in marker-facilitated selection programs. Additional index words: Quantitative genetics, Grain yield, Zea mays L., Gene action, Genetic factors, Genetic variation, Marker loci associations. I MAIZE (Zea mays L.) and other plant species, the genetic bases of quantitative traits, such as yield and most of its component traits, are normally assumed to be polygenic in nature largely because the phenotypic expressions of these traits form continuous distributions. Typically, estimates of genotypic effects associated with these traits are expressed as an average value across the genome. With the development of molecular markers (isozymes, and, more recently, restriction fragment length polymorphisms, RFLP's), the capabilities are now available for discriminating individual gene effects. Thus, numbers and genomic distribution of genetic factors (quantitative trait loci, QTL's) involved in the expression of yield and other quantitatively inherited traits can now be elucidated. Molecular marker techniques also provide the means for investigating the types and magnitudes of gene effects attributed to these QTL's. The theoretical basis for interpreting the association of marker loci with QTL's has been outlined by Mather and Jinks (1971), Tanksley, et al. (1982), Seller and Beckmann (1983), and Edwards et al. (1987). The theory exploits the fact that the marker locus serves to identify, or "mark", the chromosomal region in its vicinity and enables that region to be followed in inheritance studies. Alternative homologous chromosomal regions characterized by alternative alleles at the marker locus can be replicated extensively in different individuals and compared for quantitative trait effects, while other chromosomal regions in the same individuals and the environmental factors affecting them are permitted to vary at random. If adequate markers are available and are distributed appropriately throughout the genome, it is possible to evaluate all chromosomal regions for their effects on numerous quantitative traits of interest. A high level of linkage disequilibrium between the marker loci and QTL's is an essential feature of the approach. Earlier studies to examine the association of specific isozyme loci with grain yield in maize involved monitoring allelic frequency changes at a large number of enzyme loci in different cycles of recurrent selection experiments. In several long-term recurrent selection experiments in North Carolina, allelic frequencies at 1 Joint contribution from the USDA-ARS and the North Carolina ARS, North Carolina State Univ., Raleigh, NC. This investigation was supported in part by USDA Competitive Research Grant 83CRCR-1-1273 and in pan by Natl. Inst. of Health Res. Grant no. GM 11546 from the Natl. Inst. of General Medical Sciences of the USA. Paper no. 10644 of the Journal Series of the North Carolina ARS, Raleigh, NC. Received 11 Aug. 1986. 2 Research geneticist, USDA-ARS, and professor of genetics, North Carolina State Univ., Raleigh, NC 27695-7614; geneticist, USDAARS (now with Pillsbury Company, LeSueur, MN); and assistant professor of botany, Iowa State Univ., Ames, IA 50011. Published in Crop Sci. 27:639-648 (1987). Published July, 1987

Trait-based analyses for the detection of linkage between marker loci and quantitative trait loci in crosses between inbred lines

Abstract: Methods are presented for determining linkage between a marker locus and a nearby locus affecting a quantitative trait (quantitative trait locus=QTL), based on changes in the marker allele frequencies in selection lines derived from the F-2 of a cross between inbred lines, or in the “high” and “low” phenotypic classes of an F-2 or BC population. The power of such trait-based (TB) analyses was evaluated and compared with that of methods for determining linkage based on the mean quantitative trait value of marker genotypes in F-2 or BC populations [marker-based (MB) analyses]. TB analyses can be utilized for marker-QTL linkage determination in situations where the MB analysis is not applicable, including analysis of polygenic resistance traits where only a part of the population survives exposure to the Stressor and analysis of marker-allele frequency changes in selection lines. TB analyses may be a useful alternative to MB analyses when interest is centered on a single quantitative trait only and costs of scoring for markers are high compared with costs of raising and obtaining quantitative trait information on F-2 or BC individuals. In this case, a TB analysis will enable equivalent power to be obtained with fewer individuals scored for the marker, but more individuals scored for the quantitative trait. MB analyses remain the method of choice when more than one quantitative trait is to be analyzed in a given population.

Testing the association between polymorphic markers and quantitative traits in pedigrees.

Abstract: A statistical model that uses an iterative maximum likelihood estimation procedure is proposed for measuring and testing the association between polymorhphic genetic markers and quantitative traits in human pedigrees, after adjusting for covariates such as age and sex. The model allows the quantitative trait to have a familial correlation structure among the individuals in the sample and to follow one of a broad class of skewed or kurtotic underlying distributions. The use of the model is illustrated, and the results are compared to those using models that assume normality without any transformation and do not incorporate familial correlations.

Mapping and analysis of quantitative trait loci in Lycopersicon (tomato) with the aid of genetic markers using approximate maximum likelihood methods

Abstract: 1691 F-2 progeny of a cross between Lycopersicon esculentum and L pimpinellifolium grown under field conditions were scored for 18 quantitative traits of economic interest and 10 segregating genetic markers. Each parental strain was homozygous for one allele of each marker. Four of the markers were electrophoretic, and six were morphological. Three pairs of the genetic markers were linked. An algorithm described previously based on maximum likelihood technique was used to estimate the parameters of loci affecting the quantitative traits linked to the genetic markers and the recombination distance between quantitative trait loci and marker loci. The parameters of quantitative trait loci linked to two genetic markers were also estimated by solving for gene effect and recombination frequency from the independent equations derived from each marker. In general there was close correspondence between estimates obtained from the two methods. Except for cases where highest likelihood was obtained at complete linkage, results of the approximate maximum likelihood technique were within the parameter space, i.e. recombination frequencies between zero and 0·5 and positive variance estimates. Unreasonable results were obtained when the assumptions of the method were violated. These results support those presented previously based on simulated results and a positive control indicating that, for samples of this size, accurate estimates are derived by the maximum likelihood technique. A genetic map of quantitative trait loci is presented.

Dominance is not necessary for heterosis: a two-locus model

Abstract: Under a two-locus model with additive genes which combine multiplicatively to determine a quantitative trait, heterosis is generally observed in the F 1 It is positive only if both frequencies of the best allele at each locus are not higher in the same parental population In the F 2 , heterosis depends on the rate of recombination between the two loci If linkage is tight, F 1 superiority is nearly halved in the F 2 But if the two genes are independent, heterosis is maintained in the F 2 at the same level as in the F 1

Genetic analysis of ecological relevant morphological variability in Plantago lanceolata L. : 2. Localisation and organisation of quantitative trait loci.

Abstract: Morphological variability was analysed in an F2-generation derived from crosses between two ecotypes of Plantago lanceolata L. Six allozyme loci, localised in five linkage groups, were used as markers. For two marker loci, Got-2 and Gpi-1, segregations did not fit monogenic ratios. In the linkage groups to which these two loci belonged, male sterility genes appeared to be present. In these crosses, male sterility (type 3, as described by Van Damme 1983) may be determined by two recessive loci located in the linkage groups of Got-2 and of Gpi-1. Many correlations of morphological and life history characters with allozyme markers were observed. The quantitative trait loci did not appear to be concentrated in major gene complexes. Often many loci were involved, sometimes with effects opposite to those expected from the population values. Main effects of the linkage groups appeared to be more important than interaction effects in determining variability. It also appeared that there is a positive correlation between the number of heterozygous allozyme loci and generative growth.

Plant genetic resources: prediction by isozyme markers and ecology.

Abstract: Linkage or association of genetic markers to quantitative traits of agronomic importance can substantially simplify the genetic analysis of complex quantitative traits. Enzyme marker genes are ideal candidates for quantitative genetic analysis. We have recently applied this powerful methodology to the analysis of genetic resources of wild cereals in Israel, primarily wild emmer wheat, Triticum dicoccoides, and wild barley, Hordeum spontaneum, the progenitors of cultivated wheats and barley, respectively. We have found that allelic isozyme markers and ecological factors provide an important predictive method for identifying elite genotypes characterized by single or multiple disease resistances, high protein content, and a variety of quantitative traits of agronomic importance including germination, earliness, biomass, and yield variables. Our predictive methodology could be improved by additional crossing tests in an attempt to verify the results derived from the correlation analysis and thus establish the linkage relationships between the marker gene and the quantitative trait under discussion. This methodology, if further developed by additional isozyme and DNA markers, verified by crossing tests and gene mapping, could substantially contribute to the sampling and utilization of the genetic resources of wild gene pools for crop improvement.

A theoretical model for quantitatively inherited traits influenced by nuclear-cytoplasmic interactions.

Abstract: Cytoplasmic genes of crop species exhibit non-Mendelian inheritance and affect quantitative traits such as biomass and grain yield. Photosynthesis and respiration are physiological processes responsible, in part, for the expression of such quantitative traits and are regulated by enzymes encoded in both the cytoplasm and nucleus. Cytoplasmic genes are located in the chloroplast and mitochondrial genomes. Unlike the nuclear genome, the cytoplasmic genomes consist of single, circular, double-stranded molecules of DNA, and in many crop species, the cytoplasmic genomes are inherited solely through the maternal parent. Maternal inheritance of cytoplasmic genomes and Mendelian inheritance of the nuclear genome were used to model the genotypic value of an individual. The model then was utilized to derive genetic variances and covariances for a random-mating population. Finally, the use of reciprocal mating designs to estimate variance components was investigated.

Cloning quantitative trait loci by insertional mutagenesis.

Abstract: This study explores the theoretical potential of “insertional mutagenesis” (i.e., mutagenesis as a result of integration of novel DNA sequences into the germ line), as a means of cloning quantitative trait loci (QTL). The approach presented is based on a direct search for mutagenic effects of a quantitative nature, and makes no assumptions as to the nature of the loci affecting quantitative trait value. Since there are a very large number of potential insertion sites in the genome but only a limited number of target sites that can affect any particular trait, large numbers of inserts will have to be generated and screened. The effects of allelic variants at any single QTL on phenotype value are expected to be small relative to sampling variation. Thus two of three stages of replicate testing will be required for each insert in order to bring overall Type I error down to negligible proportions and yet maintain good statistical power for inserts with true effects on the quantitative traits under consideration. The overall effort involved will depend on the spectrum of mutagenic effects produced by insertional mutagenesis. This spectrum is presently unknown, but using reasonable estimates, about 10,000 inserts would have to be tested, at reasonable replicate numbers (n ≧ 30) and Type I error (α=0.01) in the first testing stage, to provide a high likelihood of detecting at least one insert with a true effect on a given quantitative trait of interest. Total offspring numbers required per true quantitative mutagenic effect detected decrease strongly with increased number of traits scored and increased number of inserts per initial transformed parent. In fact, it would appear that successful implementation of experiments of this sort will require the introduction of multiple independent inserts in the original parent individuals, by means of repeated transformation, or use of transposable elements as inserts. When biologically feasible, selfing would appear to be the method of choice for insert replication, and in all cases the experiments must be carried out in inbred lines to reduce error variation due to genetic segregation, and avoid confounding mutational effects of the insert with effects due to linkage with nearby segregating QTL. The special qualifications of Arabidopsis thaliana for studies of this sort are emphasized, and problems raised by somaclonal variation are discussed.

Biochemical polymorphism in relation to performance in horses

Abstract: Investigations on relationships between biochemical polymorphism and variation in quantitative traits are of interest from the perspectives of both theoretical quantitative genetics and practical animal breeding. This subject was studied by using racing performance records of more than 25,000 horses of the Swedish Trotter breed born in the period 1970–1979. For all horses data on six blood group and nine electrophoretic loci were available. Two different performance traits were investigated. A racing performance index value was calculated for all individuals which had started in at least five races. Horses which had not started at all or less than five times were pooled in an unstarted class and the proportion of started horses was analysed as an all-or-none trait. The relationships between the marker genes and these two performance traits were analysed statistically by using linear models. Analysis within sires revealed a very highly significant association between variation at the serum esterase locus (Es) and the proportion of started horses. In addition, four weakly significant associations were found. A striking feature of the highly significant association involving the esterase locus was that the effect of different alleles showed a good fit to an additive genetic model as the value of each heterozygous type was intermediate to the two corresponding homozygotes. In addition to the association tests, the possibility of genetic linkage between marker genes and genes affecting performance was tested as well as the influence on performance of heterozygosity at marker loci. No significant relationships were revealed in these latter tests.

Linkage between quantitative and marker loci. V. Joint analysis of various marker and quantitative traits

Abstract: New versions are suggested to analyse marker and quantitative characters combinations. Possible modes of application of the algorithms developed for recombination analysis are discussed, including: 1) the estimation of crossing-over frequency between markers with incomplete penetrance, 2) the quantitative character variability account to analyse genetic interference, 3) search for genetic factors affecting a set of quantitative characters, 4) the evaluation of differences between male and female meiosis at the crossingover level etc.

Selection against PSS by means of Blood Typing

Abstract: The discoveries leading to establishment of the 6-locus linkage group Phi, Hal, S, H, Po2, Pgd are reviewed. The halothane locus, Hal, is a major quantitative trait locus, QTL, affecting the porcine stress syndrome, PSS, and associated meat quality traits. The five loci closely linked to the Hal locus are useful for marker assisted selection, MAS, against the recessive Haln gene and, thereby, against PSS. Application of MAS to population data, in contrast to family data, requires linkage disequilibrium between the Hal genes and the marker genes considered. Examples of selection are presented. The usefulness of haplotyping within families for distinguishing between halothane NN and Nn genotypes is emphasized. Attention is called to complications due to heterozygous advantage of the Hal genes. The efficiency of selection based on halothane tests alone versus halothane tests combined with blood typing remains to be evaluated. The need for, and possibility of, exact heterozygosity-diagnosis is discussed. Finally, the view is expressed that animal welfare problems should not be ignored whenever eradication or exploitation of the halothane gene is considered.

Estimation of genetical parameters for a quantitative trait subject to major gene influences.

Abstract: Both regression and correlation estimates of genetical variance and heritability for a quantitative trait influenced by a major gene can be obtained from the error variance-covariance matrix of MANOVA using relative-relative phenotype pairs as factors. The method is illustrated with parent-offspring data on red cell acid phosphatase phenotypes and serum acid phosphatase activity.