Interpreting nonsignificant outcomes of heterogeneity tests in gene mapping.
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Two-way network crosses are often related to indigenous breeds which have two notable characteristics: 1. individuals within-breed are different, 2. the differences between-breeds are different too. Because of this, regular Least-square analysis method can not be used in this type of test. This paper proposed a new method, which was based on the new model and the best liner unbiased estimation theory. An example was given to show the usage.
The study included 82 individuals. Twenty-two were sporadic unrelated patients with Primary Congenital Glaucoma (PCG), and 60 were the members of 10 multiplex families. They were enrolled into two groups; GI:10 multiplex families; GII:32 unrelated patients with PCG (22 sporadic plus 10 probands of the multiplex families). The following were carried out for all the individuals: (1) detailed history; (2) ophthalmologic examination for diagnosis of PCG; (3) clinical examination to exclude any other disease; (4) HLA antigen typing using 30 antigens, 9 for A locus, 15 for B locus, and 6 for DR locus. Genetic and statistical analysis revealed the following: (1) significant association between HLA-B8 and PCG; (2) family studies revealed a susceptibility gene, probably recessive, predisposing to PCG; (3) this gene is linked to HLA, with strong linkage disequilibrium with B8.
A significant difference between blacks and whites in the distribution of red cell galactokinase (GALK) has been found by Tedesco et al. [2]. From the shapes of the distributions, it was inferred that whites are essentially all homozygous for one allele (GALKA), but blacks are polymorphic. A second allele (GALKP), for lower GALK activity, is presented at high frequency in blacks but rare or absent in whites. This paper presents a method which, assuming the genetic model presented, estimates the genotype composition of the black sample. We make some reasonable biochemical assumptions and fit a mixture of three normal distributions to the black data to obtain an estimate of p, the frequency of GALKA in blacks. The fit of the model to the data is excellent and the best estimate of p is .217 +/- .025. Since admixture of white genes in blacks from the United States is known to be about 20%, the value of p implies that virtually all GALKA alleles were introduced by admixture, and that the ancestral black population was monomorphic for GALKP. If whites are indeed monomorphic for GALKA, they differ from unmixed blacks by a full gene substitution at the locus for GALK.
In the course of long-term experiment on domestication of silver fox, it was necessary to determine the most important behavioral features, selection for which would give domestication effect. The mathematical method of principal components was used for the analysis of 20 fox behavior traits. The combination of the initial traits which reflected the structure of the integral trait, i.e. domesticated type of behavior, was determined. The practical use of this combination seems to more adequately estimate the level of domestication of a given animal, which is indispensable for subsequent effective selection.
It is very important to be able to distinguish between selectively significant genetic variability and selectively-neutral one for quantitative analysis of genetic differentiation in human (and any other) populations. The key to the problem is to determine a start-point for detection of neutral genetic variability, which will help to establish alignment of adaptive and neutral forces operating in genetic differentiation. The purpose of this work is to adduce proofs in favour of mean Fst value for a sample of gene loci as of the start-point for measuring neutrality level of genetic differentiation. These proofs came from various demographic and onomastic characteristics of ethnic groups as well as from genetic chronology of ethnic history which is in good concordance with actual historical chronology of ethnic groups. Once the start-point for testing neutrality is determined, it becomes possible to reveal the selective pressure to which various human genes are undergone and to elucidate adaptive structure of mankind's genetic pool. It was shown that only 15 alleles from 49 belonging to 20 polymorphic loci can be considered selectively neutral.
Estimation of recombination fractions and interference coefficients is of importance in multilocus linkage analysis. With the development of molecular genetic technologies such as RFLP, multilocus data are readily available to researchers. Several methods have been developed to analyze such data, and each performs well under restrictive conditions. The present paper proposes a method based on a multiplicative model and maximum-likelihood estimation of recombination fractions and interference coefficients. The estimators are consistent regardless of the model assumptions and are efficient if the model is a good approximation. The estimators are tractable even when there are incomplete observations. Furthermore, the interference between nonadjacent chromosomal regions or those among three chromosomal regions can be modeled and tested by a simple Z-test. The proposed method was applied to linkage analysis of four-locus data obtained from Drosophila and that of seven-locus data obtained again from Drosophila. Reanalysis of the first example revealed that there is interference between chromosomal regions 2 and 3. Analysis of the second example suggested that there is triple interference as well as pairwise interference between nonadjacent chromosomal regions; the genetic interpretation of these findings remains to be developed.
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A strong criticism of raw data analysis in DNA/DNA hybridization studies (Marks et al., 1988; Sarich et al., 1989) states that a widely used statistic, T50H, can in some cases lead to spurious conclusions, as exemplified by some hominoid and bird DNA/DNA results found in Sibley and Ahlquist (1987a, b). To test this criticism and compare the phylogenetic information deduced from several alternative methods of analysis, I have re-analysed the melting curves of more than 150 hybrid comparisons among muroid rodents, including almost all of my previously published data (Catzeflis et al. 1987). Four major statistics have been compared: Mode, Tm, T50H and NPH (for definitions of terms: see Sibley and Ahlquist 1981). Although the T50H statistic was found to be more variable when compared to Mode and Tm, confirming the claims of Sarich et al. (1989), it nevertheless appeared to be, under certain technical conditions, the method of choice for analyzing distantly related hybrids. The Mode and Tm appeared to be the best indexes of genomic dissimilarity for analyzing more similar genomes. The use of Tm is not very useful for comparing dissimilar genomes, as its range of efficient use was shown to be much more limited towards the lower temperatures (i.e., -larger delta-values) than for the Mode. Mode was found to be the statistic of choice because of i) its large range of application (up to delta-Mode values of 18-20 degrees C), ii) its reproducibility, and iii) its consistency between experiments and in reciprocal comparisons. For the data set on which our earlier conclusions concerning the very rapid rate of DNA change in muroid rodents (Catzeflis et al., 1987) were based, it appears that Mode, Tm and T50H do yield similar conclusions as far as the evolutionary tree of the muroid rodents is concerned. The fourth index, which is the Normalized Percent of Hybridization, appears to be strongly affected by experimental conditions, and should be used with caution.
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Cytological evidence indicates that genetic interference can be partitioned into two empirical components: nonrandomness in the number of chiasmata that occur and nonrandomness in the locations of multiple chiasmata. Previous studies have incorporated the first effect into genetic models for analyzing multipoint data. An extension to this approach is presented which allows for the second component of interference by modeling the probability density function of the locations of multiple crossovers. Results of reanalyses of multilocus data for the Drosophila X chromosome show that models that incorporate only the first effect give a better fit to these data than do standard mapping functions and that the extended model significantly improved the fit by decreasing the predicted frequency of multiple crossovers in nearby regions. Our results demonstrate that chiasma-based models of multilocus recombination, which are unique in incorporating direct estimates of the frequency of multiple crossovers for a chromosome region, can provide a powerful and realistic means of accounting for genetic interference when applied to the problems of gene localization, locus ordering, and exclusion mapping.
Initial and accurate inference of locus order and estimates of interlocus distances and interference can be obtained using seriation techniques. The analysis requires a matrix of recombination values that can be estimated by standard pairwise linkage analysis. This allows combination of results from individual investigators without reanalysis of basic pedigree material. Seriation can be performed without the use of a computer.
The analysis of multipoint data in humans involves detection of linkage, inferences about order, and estimation of map lengths. In order to calculate likelihoods, it is necessary to have predictive formulas for multiple recombination frequencies. In the present study the Markovian assumption of Morton and MacLean is generalized to give predictive formulas for multiple-region recombination using realistic map functions. The best-fitting map functions have been determined by fitting the nine-locus data of Morgan et al. and the seven-locus data of Weinstein on the Drosophila X chromosome. Two map functions fit the data better than other published functions: that of Rao et al. with a map parameter of P = .33 and a new function suggested in the present paper. The close agreement of the estimate of the mapping parameter with a previous estimate inferred from human male meiosis suggests that the map function is robust. A further improvement in the fit to the data can be obtained by the addition of a second parameter to reduce the expected number of multiple recombinants. By comparison with the map functions recommended in the present paper, the assumption of no interference gives a poor fit to the data.
A multifactorial model incorporating temporal trends in its parameters is discussed. The model is a generalization of the tau model of Rice et al. in which the parameters are assumed to be specific functions of time. A special case of this model is fit to data on height, weight, and Quetelet index in 1,067 nuclear families to demonstrate the utility of the approach. The results indicate that there is considerable temporal variation in family resemblance over time for all three traits. For height and Quetelet index, both the transmissibility, comparable to heritability, and residual sibling environmental correlation show temporal changes, while for weight, only the latter exhibits significant trends. Trends were not found in the marital correlation for any of the traits, and only limited evidence was found for trends in the maternal transmission parameter for height. This provides an objective method for evaluating the nature and sources of temporal trends in family resemblance, which can easily be incorporated into the framework of any model-based approach.
The familial form of myasthenia gravis is a relatively rare condition, occurring in about 3.4 per cent of myasthenic patients. Two familial cases with ocular myasthenia gravis are reported. They had a third brother who died probably with the same disease. Their parents are cousins. The authors made a brief approach of genetic, clinical, statistical and therapeutic aspects of the disease.
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