Aid Of Genetic Markers Research Articles

Identification of toxigenic Cyanobacteria of the genus Microcystis in the Curonian Lagoon (Baltic Sea)

In 2002–2008, seasonal (April–November) monitoring of the phytoplankton in the Russian part of the Curonian Lagoon at five fixed sites was performed. A total of 91 Cyanobacteria, 100 Bacillariophyta, 280 Chlorophyta, 21 Cryptophyta, and 24 Dinophyta species were found. Six potentially toxic species of cyanobacteria: Aphanizomenon flos-aquae, Anabaena sp., Microcystis aeruginosa, M. viridis, M. wesenbergii, and Planktothrix agardhii dominated the phytoplankton biomass and caused water blooms. The seasonal average phytoplankton biomass ranged from 30 to 137 g/m3. The cyanobacteria’s biomass varied from 10 to 113 g/m3 forming 30–82% of the total with a mean of 50%. With the aid of genetic markers (microcystin (mcy) and nodularin synthetases), six variants of the microcystin-producing gene mcyE from the genus Microcystis were identified. Due to the intensive and lengthy blooms of potentially toxic and toxigenic cyanobacteria, the environmental conditions in the Curonian Lagoon appear unfavorable. The water should be monitored for cyanotoxins with analytical methods in order to determine if the area is safe for recreational use.

Semiparametric Methods for Mapping Quantitative Trait Loci with Censored Data

Statistical methods for the detection of genes influencing quantitative traits with the aid of genetic markers are well developed for normally distributed, fully observed phenotypes. Many experiments are concerned with failure-time phenotypes, which have skewed distributions and which are usually subject to censoring because of random loss to follow-up, failures from competing causes, or limited duration of the experiment. In this article, we develop semiparametric statistical methods for mapping quantitative trait loci (QTLs) based on censored failure-time phenotypes. We formulate the effects of the QTL genotype on the failure time through the Cox (1972, Journal of the Royal Statistical Society, Series B 34, 187-220) proportional hazards model and derive efficient likelihood-based inference procedures. In addition, we show how to assess statistical significance when searching several regions or the entire genome for QTLs. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. Applications to two animal studies are provided.

Pleiotropic QTL Analysis

Statistical methods for the detection of genes influencing quantitative trait (QTLs) with the aid of genetic markers are well developed for the analysis of a single trait. In practice, many experimental data contain observations on multiple correlated traits and methods that permit joint analysis of all traits are now required. Generalization of the maximum likelihood method to a multitrait analysis is a good approach, but the increase in complexity, due to the number of parameters to be estimated simultaneously, could restrain its practical use when the number of traits is large. We propose an alternative method based on two separate steps. The first step is to estimate the (co)variance matrix of the traits and use this estimate to obtain the canonical variables associated to the traits. The second step is to apply a single-trait maximum likelihood method to each of the canonical variables and to combine the results. Working in a local asymptotic framework for the effects of the putative pleiotropic QTL, i.e., for a pleiotropic QTL whose effect is too small to be detected with certainty, we prove that the combined analysis with canonical variables is asymptotically equivalent to a multitrait maximum likehood analysis. A threshold for the mapping of the pleiotropic QTL is also given. The probability of detecting a QTL is not always increased by the addition of more correlated traits. As an example, a theoretical comparison between the power of a multitrait analysis with two variables and the power of a single-trait analysis is presented. Experimental data collected to study the polygenic resistance of tomato plants to bacterial wilt are used to illustrate the combined analysis with canonical variables.

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

Application of a canonical transformation to detection of quantitative trait loci with the aid of genetic markers in a multi-trait experiment

Effects of individual quantitative trait loci (QTLs) can be isolated with the aid of linked genetic markers. Most studies have analyzed each marker or pair of linked markers separately for each trait included in the analysis. Thus, the number of contrasts tested can be quite large. The experimentwise type-I error can be readily derived from the nominal type-I error if all contrasts are statistically independent, but different traits are generally correlated. A new set of uncorrelated traits can be derived by application of a canonical transformation. The total number of effective traits will generally be less than the original set. An example is presented for DNA microsatellite D21S4, which is used as a marker for milk production traits of Israeli dairy cattle. This locus had significant effects on milk and protein production but not on fat. It had a significant effect on only one of the canonical variables that was highly correlated with both milk and protein, and this variable explained 82% of the total variance. Thus, it can be concluded that a single QTL is affecting both traits. The effects on the original traits could be derived by a reverse transformation of the effects on the canonical variable.

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

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.

Maximum Likelihood Techniques for the Mapping and Analysis of Quantitative Trait Loci with the Aid of Genetic Markers

A method is presented to estimate the biometric parameters of a quantitative trait locus linked to a genetic marker when both loci are segregating in the F-2 generation of a cross between two inbred lines. The method, which assumes underlying normal distributions, is a combination of maximum likelihood and moments methods and uses the statistics of the genetic marker genotype samples for the quantitative trait to estimate the recombination frequency between the two loci and the means and variances of the genotypes of the quantitative trait locus. With this method, the genetic parameters of a locus affecting plant height linked to an electrophoretic marker for esterase were accurately estimated from a sample of 1596 F-2 progeny of a cross between two species of Lycopersicon (tomato). Linkage distance between the two loci was 38 map units and the effect of the quantitative trait locus was 1.6 phenotypic standard deviation units. Accurate estimates of the genetic parameters and linkage distance for populations of 2000 individuals simulated with a segregating codominant locus with an effect of 1.63 standard deviations linked to a genetic marker with .2 recombination were also derived by this method. The method is not effective in distinguishing between complete and partial linkage in samples of only 500 individuals or for quantitative loci with effects less than a phenotypic standard deviation. The method is more effective for codominant than for dominant loci.

The Effect of Ploidy on the Stability of Plasmodial Heterokaryons in Physarum polycephalum

The stability of actively growing heterokaryons made by fusing haploid and diploid plasmodia of Physarum polycephalum has been investigated with the aid of genetic markers affecting plasmodial colour and amino acid requirements. All heterokaryons initially expressed the dominant alleles present in both component plasmodia, but after a few subcultures every heterokaryon synthesized from a haploid plus a diploid plasmodium changed to express the recessive alleles carried by the haploid component. In contrast, heterokaryons synthesized from combinations of haploid plasmodia remained stable throughout many subcultures. No evidence was found for the segregation of incompatibility alleles responsible for heterokaryon instability, although the possibility could not be excluded that a gene closely linked to matA was involved. A direct test of the effect of ploidy on heterokaryon stability was carried out, in which the use of isogenic haploid and diploid plasmodia allowed the effect of incompatibility genes to be eliminated. Again the phenotype of every haploid plus diploid heterokaryon changed to that of the haploid component, whereas haploid plus haploid heterokaryons remained stable. Variations in the relative sizes of the haploid and diploid plasmodia altered the speed, but not the direction, of the changes observed. Analysis of progeny indicated that the changes in phenotype were due to loss of diploid nuclei from the heterokaryons.

Selection for improved meat quality with the aid of genetic markers in Pigs of the Danish Landrace Breed

(1979). Selection for improved meat quality with the aid of genetic markers in Pigs of the Danish Landrace Breed. Acta Agriculturae Scandinavica: Vol. 29, No. 3, pp. 291-294.