The effect of pollen irradiation on segregation in spring barley crosses

Observations on the Ml, M2 and M3 generations from three barley crosses confirmed that pollen irradiation can cause deviations from expected segregation ratios for certain characters. The reduced fertility observed in the Ml and M2 generations of these crosses could be problematical in breeding programmes. It was of particular interest that at the highest dose rate used for the cross TS117 × Scots Bere there was no expression of the 6-row character, which is controlled by a recessive paternal factor.     

A gene-model-free method for linkage analysis of a disease-related-trait based on analysis of proband/sibling pairs

In this paper we investigate the power of finding linkage to a disease locus through analysis of the disease-related traits. We propose two family-based gene-model-free linkage statistics. Both involve considering the distribution of the number of alleles identical by descent with the proband and comparing siblings with the disease-related trait to those without the disease-related-trait. The objective is to find linkages to disease-related traits that are pleiotropic for both the disease and the disease-related-traits. The power of these statistics is investigated for Kofendrerd Personality Disorder-related traits a (Joining/founding cults) and trait b (Fear/discomfort with strangers) of the simulated data. The answers were known prior to the execution of the reported analyses. We find that both tests have very high power when applied to the samples created by combining the data of the three cities for which we have nuclear family data.     

The effect of shoal size on patterns of body colour segregation in mollies

Individual white and black mollies Poecilia latipinna spent significantly more time near the larger group when given the choice between two shoals of similar colouration to themselves. When given the choice between a large and a small shoal of dissimilar colouration to themselves, black test fish spent significantly more time with the larger shoal while white test fish showed no preference for either group. Both white and black mollies chose the smaller of two shoals when given the choice between a large dissimilarly coloured shoal and a small similarly coloured shoal. The results indicate that mollies actively discriminate between shoals on the basis of both body colour and shoal size. However, body colour segregation appears to have a stronger influence on shoal choice.     

Complex segregation analysis of hypospadias

Hypospadias, when the urethra opens on the ventral side of the penis, is a common malformation seen in about 3 per 1000 male births. It is considered a complex disorder with both genetic and environmental factors involved in the pathogenesis. Low birth weight is known to be an important risk factor for hypospadias, but several observations speak in favour of genetic factors as well. In order to delineate the relative contribution of the genetic factors behind hypospadias, we performed a complex segregation analysis of 2005 pedigrees in Sweden. The probands were ascertained through the departments of paediatric surgery and departments of plastic surgery and urology in Sweden where boys with hypospadias undergo surgery. In 7% of the ascertained families one or more additional cases of hypospadias were present. The complex segregation analysis showed a heritability of 0.99 and evidence for multifactorial inheritance. The results suggest that hypospadias might be due to monogenic effects in a small proportion of the families, but that there is a multifactorial cause for the majority of the cases.     

Genetic analysis of juvenile periodontitis in families ascertained through an affected proband.

Data from 28 families ascertained through a proband with juvenile periodontitis were used to test a series of Mendelian models of inheritance that included both autosomal and X-linked transmission. There was strong evidence of familial aggregation of this progressive dental disease, and the best-fitting model was an autosomal recessive model. Because of the rather limited age range for expression of the disease in this situation, simulations were done, in a model-choice analysis using samples of this size, to assess the chance of mistaking an autosomal dominant disease (with masking of the affected phenotype outside a specified age range) for an autosomal recessive disease. While the rate of Type II error was fairly high (40%) when competing models in these simulations were compared, these data suggest that it is reasonable to infer that juvenile periodontitis is an autosomal recessive disorder.     

Sample-size calculations in segregation analysis

Segregation analysis, employing nuclear families, is the most frequently used method to evaluate the mode of inheritance of a trait. To our knowledge, there exists no tabular information regarding the sample sizes required of individuals and families needed to perform a significance test of a specific segregation ratio for a predetermined power and significance level. To fill this gap, we have developed sample-size tables based on the asymptotic variance of the maximum likelihood estimate of the segregation ratio and on the normal approximation for two-sided hypothesis testing. Assuming homogeneous sibship size, minimum sample sizes were determined for testing the null hypothesis for the segregation ratio of 1/4 or 1/2 vs. alternative values of .05-.80, for the significance level of .05 and power of .8, for ascertainment probabilities of nearly 0 to 1.0, and sibship sizes 2-7. The results of these calculations indicate a complex interaction of the null and the alternate hypotheses, ascertainment probability, and sibship size in determining the sample size required for simple segregation analysis. The accompanying tables should aid in the appropriate design and cost assessment of future genetic epidemiologic studies.     

Complex segregation analysis of diabetes mellitus

Complex segregation analysis was applied to a sample of 12,293 nuclear families each with at least 1 diabetic patient. The families were divided into two groups depending on the proband's treatment: insulin-dependent (IDG) and insulin-independent (IIG). Heterogeneity analysis has revealed a highly significant difference in the IIG group when families were divided into different mating types. The higher recurrence risk was found in the group with affected mothers. Also evidence for a major recessive gene was found in the IGG group, while it was not possible to distinguish between the hypothesis for absence of a major locus and absence of polygenic inheritance in the IDG group. Risks to develop the disease were calculated for a few typical situations.     

Complex segregation analysis of autism.

A complex segregation analysis of autism in 185 Utah families was carried out using the mixed model. The 209 affected individuals in these families represent nearly complete ascertainment of the autistic cases born in Utah between 1965 and 1984. The sibling recurrence risk for autism was 4.5% (95% confidence limits 2.8%-6.2%). Likelihoods were maximized for major-gene models, a polygenic model, a sibling-effect model, and a mixed model consisting of major-gene and shared-sibling effects. The analysis provided no evidence for major-locus inheritance of autism. Subdivision of the sample according to the probands' IQ levels showed that sibling recurrence risk did not vary consistently with IQ level. A segregation analysis of families in which the proband had an IQ less than 50 also failed to provide evidence for a major locus. However, because of the etiologic heterogeneity of this disorder, genetic analysis of other meaningful subsets of families could prove informative.     

The EIM algorithm in the joint segregation analysis of quantitative traits

In this article, a new algorithm for obtaining the maximum likelihood estimators (MLEs) of parameters in the joint segregation analysis (JSA) of multiple generations of P1, F1, P2, F2 and F2:3 (MG5) for quantitative traits was set up. Firstly, owing to the fact that the component variance of the heterogeneous genotype in F2:3 included both the first-order genetic parameters (denoted by the means of distributions) and the second-order parameters, a simple closed form for the MLEs of the means of component distributions did not exist while the expectation and maximization (EM) algorithm was used. To simplify the estimation of parameters, the first partial derivative of the above variance on the mean in the sample log-likelihood function was omitted. However, this would be remedied by the iterated method. Then, variances of component distributions for segregating populations were partitioned into major-gene, polygenic and environmental variances so that the generally iterated formulae for estimating the means as well as polygenic and environmental variances of component distributions in the maximization step (M-step) of the EM algorithm were obtained. Therefore, the EM algorithm for estimating parameters in the JSA model for the MG5 was simplified. This is called the expectation and iterated maximization (EIM) algorithm. Finally, an example of the inheritance of the resistance of soybean to beanfly showed that the results of mixed inheritance analysis in this paper coincided with those in both Wang & Gai (2001) and Wei et al. (1989), so the EIM algorithm was appropriate.     

Torus palatinus: a segregation analysis

Segregation analysis of 99 sibships in 2 samples from Venezuela and Japan indicates that a torus palatinus is inherited in simple dominant fashion. The gene shows variable expressivity and penetrance close to 85%, without significant heterogeneity between the populations considered. No evidence of sporadic cases has been found.     

A sampling algorithm for segregation analysis

Methods for detecting Quantitative Trait Loci (QTL) without markers have generally used iterative peeling algorithms for determining genotype probabilities. These algorithms have considerable shortcomings in complex pedigrees. A Monte Carlo Markov chain (MCMC) method which samples the pedigree of the whole population jointly is described. Simultaneous sampling of the pedigree was achieved by sampling descent graphs using the Metropolis-Hastings algorithm. A descent graph describes the inheritance state of each allele and provides pedigrees guaranteed to be consistent with Mendelian sampling. Sampling descent graphs overcomes most, if not all, of the limitations incurred by iterative peeling algorithms. The algorithm was able to find the QTL in most of the simulated populations. However, when the QTL was not modeled or found then its effect was ascribed to the polygenic component. No QTL were detected when they were not simulated.     

General models for segregation analysis.

Theoretical details are given of various oligogenic models for segregation analysis that are available as a general segregation analysis ("GENSEG") package, programmed in FORTRAN iv. The models allow for up to two autosomal loci and one X-linked locus, normally distributed or dichotomous phenotypes, variable age of onset, and various ascertainment functions (including one that allows the probability of becoming a proband to be dependent on the age of onset). Current programs are limited to the analysis of 2-generational data, using the joint likelihood of the sibship and parental phenotypes, unless it can be assumed that the pedigrees being analyzed are a random sample from the population; half-sibships and twins, however, are explicitly allowed.     

Effects of implicit parameters in segregation analysis

In human genetic analysis, data are collected through the so-called 'ascertainment procedure'. Statistically this sampling scheme can be thought of as a multistage sampling method. At the first stage, one or several probands are ascertained. At the subsequent stages, a sequential sampling scheme is applied. Sampling in such a way is virtually a nonrandom procedure, which, in most cases, causes biased estimation which may be intractable. This paper focuses on the underlying causes of the intractability problem of ascertained genetic data. Three types of parameters, i.e. target, design and nuisance parameters, are defined as the essences to formulate the true likelihood of a set of data. These parameters are also classified into explicit or implicit parameters depending on whether they can be expressed explicity in the likelihood function. For ascertained genetic data, a sequential scheme is regarded as an implicit design parameter, and a true pedigree structure as an implicit nuisance parameter. The intractability problem is attributed to loss of information of any implicit parameter in likelihood formulation. Several approaches to build a likelihood for estimation of the segregation ratio when only an observed pedigree structure is available are proposed.     

Pedigree analysis of plasmid segregation in yeast

We have used pedigree analysis to investigate the mitotic segregation of circular and linear DNA plasmids in Saccharomyces cerevisae. Circular ARS plasmids, which bear putative chromosomal replication origins, have a high segregation frequency and a strong bias to segregate to the mother cell at mitosis. The segregation bias explains how the fraction of plasmid-bearing cells can be small despite the high average copy number of circular ARS plasmids. Linear ARS plasmids do not show strong segregation bias, nor does the 2 mu ori-containing plasmid YEp 13, when it is present in strains containing intact 2 mu circles. In the absence of endogenous 2 mu circles, YEp 13 behaves like an ARS plasmid, showing a strong maternal segregation bias. The presence of a centromere on circular ARS plasmids eliminates segregation bias. We discuss a model for plasmid segregation, which explains these findings and the possible biological significance of mother-daughter segregation bias.