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PubMedDate not supplied

Genetics of human body size and shape: complex segregation analysis.

The genetic component in a mixed heritability model, including major gene, multifactorial and sibling environment transmissible components, was studied for some 20 anthropometric traits in two ethnically different samples. The first sample comprised 305 Mexican nuclear families, and the second comprised 83 Ashkenazi Jewish nuclear families living in Israel. All variables, after adjustment for age and sex, were subjected to principal-components analysis (PCA) in each sample separately. The mixed model of inheritance as implemented in the computer program POINTER was used in the present study. An attempt was made to evaluate genetic effects in the variation of the first principal components (PCs). PCA showed a clear separation of variables and was easily interpretable. The PC1 was a credibly general size factor. This factor alone accounted for about 30% of the total variance. Other components are rather shape factors for various combinations of traits. The testing of several genetic hypothesis showed the following: (1) For all factor scores the genetic component was high and statistically significant. (2) In a Mexican sample, for PC1 and PC2, both major gene and polygenes contributed significantly to the total variation of these variables; in the major locus the alleles were most probably codominant. (3) For all other PCs the major gene effect hypothesis was rejected, with more than 50% of the variation attributable to the polygenes contribution. (4) No evidence was found for sibling environmental resemblance in either sample.

Adolescent↗
PubMed1993

Strategies for the molecular genetic analysis of obesity in humans.

Studies of twins, adopted children, and some human populations indicate that body composition is significantly influenced by genetic factors. However, in no specific instance in either man or animals is the precise etiology of obesity known at the molecular level. Attempts to identify the molecular basis of obesity in humans have been hampered by difficulties in measuring food intake and energy expenditure with sufficient accuracy, as well as the apparent polygenic control of body composition in man. These constraints have stimulated interest in inbred animal strains, particularly mice, that have a genetic predisposition to obesity. Using the techniques of positional cloning, molecular markers flanking two autosomal recessive mouse obesity mutants (ob and db), which demonstrate a metabolic/behavioral phenotype similar to that observed in obese humans, have been identified. These markers are being used: (1) as starting points for chromosome walks to identify these genes, (2) as an aid in identifying genetically obese rodents prior to the development of the experimentally confounding obese phenotype, and (3) to investigate the possible contribution of the ob and db gene products to obesity in families segregating an obese phenotype. Additionally, genetic crosses segregating these obesity mutations are being used to identify "polygenes" that influence the severity of obesity and type II diabetes. Such studies may ultimately lead to the characterization of genes that influence the development and severity of obesity and non-insulin-dependent diabetes (NIDDM) in humans.

Animals↗
PubMed1999

Comparison of linkage-disequilibrium methods for localization of genes influencing quantitative traits in humans.

Linkage disequilibrium has been used to help in the identification of genes predisposing to certain qualitative diseases. Although several linkage-disequilibrium tests have been developed for localization of genes influencing quantitative traits, these tests have not been thoroughly compared with one another. In this report we compare, under a variety of conditions, several different linkage-disequilibrium tests for identification of loci affecting quantitative traits. These tests use either single individuals or parent-child trios. When we compared tests with equal samples, we found that the truncated measured allele (TMA) test was the most powerful. The trait allele frequencies, the stringency of sample ascertainment, the number of marker alleles, and the linked genetic variance affected the power, but the presence of polygenes did not. When there were more than two trait alleles at a locus in the population, power to detect disequilibrium was greatly diminished. The presence of unlinked disequilibrium (D'*) increased the false-positive error rates of disequilibrium tests involving single individuals but did not affect the error rates of tests using family trios. The increase in error rates was affected by the stringency of selection, the trait allele frequency, and the linked genetic variance but not by polygenic factors. In an equilibrium population, the TMA test is most powerful, but, when adjusted for the presence of admixture, Allison test 3 becomes the most powerful whenever D'*>.15.

Alleles↗
PubMed2000

Hormonal carcinogenesis.

Hormone-related cancers, namely breast, endometrium, ovary, prostate, testis, thyroid and osteosarcoma, share a unique mechanism of carcinogenesis. Endogenous and exogenous hormones drive cell proliferation, and thus the opportunity for the accumulation of random genetic errors. The emergence of a malignant phenotype depends on a series of somatic mutations that occur during cell division, but the specific genes involved in progression of hormone-related cancers are currently unknown. In this review, the epidemiology of endometrial cancer and breast cancer are used to illustrate the paradigms of hormonal carcinogenesis. Then, new strategies for early detection and prevention of hormonal carcinogenesis are discussed. This includes developing polygenic models of cancer predisposition and the further development of safe and effective chemopreventives that block target sequence activity. We developed polygenic models for breast and prostate cancer after hypothesizing that functionally relevant sequence variants in genes involved in steroid hormone metabolism and transport would act together, and also interact with well-known hormonally related risk factors, to define a high-risk profile for cancer. A combination of genes each with minor variation in expressed activity could provide a degree of separation of risk that would be clinically useful as they could yield a large cumulative difference after several decades. The genes included in the breast cancer model are the 17beta-hydroxysteroid dehydrogenase 1 (HSD17B1) gene, the cytochrome P459c17alpha (CYP17) gene, the aromatase (CYP19) gene, and the estrogen receptor alpha (ER) gene. The prostate cancer model includes the androgen receptor gene (AR), steroid 5alpha-reductase type II (SRD5A2), CYP17 and the 3beta hydroxysteroid dehydrogenase (HSD3B2) gene. We present data from our multi-ethnic cohort to support these models.

Breast Neoplasms↗
PubMed1993

A method of screening for genes of major effect.

This paper describes a method for screening animal populations on an index of calculated probabilities of genotype status at an unknown single locus. Animals selected by such a method might then be candidates in test matings and genetic marker analyses for major gene detection. The method relies on phenotypic measures for a continuous trait plus identification of sire and dam. Some missing phenotypes and missing pedigree information are permitted. The method is an iterative two-step procedure, the first step estimates genotype probabilities and the second step estimates genotypic effects by regressing phenotypes on genotype probabilities, modeled as true genotype status plus error. Prior knowledge or choice of major locus-free heritability for the trait of interest is required, plus initial starting estimates of the effect on phenotype of carrying one and two copies of the unknown gene. Gene frequency can be estimated by this method, but it is demonstrated that the consequences of using an incorrect fixed prior for gene frequency are not particularly adverse where true frequency of the allele with major effect is low. Simulations involving deterministic sampling from the normal distribution lead to convergence for estimates of genotype effects at the true values, for a reasonable range of starting values, illustrating that estimation of major gene effects has a rational basis. In the absence of polygenic effects, stochastic simulations of 600 animals in five generations resulted in estimates of genotypic effects close to the true values. However, stochastic simulations involving generation and fitting of both major genotype and animal polygenic effects showed upward bias in estimates of major genotype effects. This can be partially overcome by not using information from relatives when calculating genotype probabilities-a result which suggests a route to a modified method which is unbiased and yet does use this information.

Alleles↗
PubMed1994

Genetic characterization of pathogenic Saccharomyces cerevisiae isolates.

Saccharomyces cerevisiae isolates from human patients have been genetically analyzed. Some of the characteristics of these isolates are very different from laboratory and industrial strains of S. cerevisiae and, for this reason, stringent genetic tests have been used to confirm their identity as S. cerevisiae. Most of these clinical isolates are able to grow at 42 degrees, a temperature that completely inhibits the growth of most other S. cerevisiae strains. This property can be considered a virulence trait and may help explain the presence of these isolates in human hosts. The ability to grow at 42 degrees is shown to be polygenic with primarily additive effects between loci. S. cerevisiae will be a useful model for the evolution and genetic analysis of fungal virulence and the study of polygenic traits.

Crosses, Genetic↗
PubMed1994

Use of multiple genetic markers in prediction of breeding values.

Genotypes at a marker locus give information on transmission of genes from parents to offspring and that information can be used in predicting the individuals' additive genetic value at a linked quantitative trait locus (MQTL). In this paper a recursive method is presented to build the gametic relationship matrix for an autosomal MQTL which requires knowledge on recombination rate between the marker locus and the MQTL linked to it. A method is also presented to obtain the inverse of the gametic relationship matrix. This information can be used in a mixed linear model for simultaneous evaluation of fixed effects, gametic effects at the MQTL and additive genetic effects due to quantitative trait loci unlinked to the marker locus (polygenes). An equivalent model can be written at the animal level using the numerator relationship matrix for the MQTL and a method for obtaining the inverse of this matrix is presented. Information on several unlinked marker loci, each of them linked to a different locus affecting the trait of interest, can be used by including an effect for each MQTL. The number of equations per animal in this case is 2m + 1 where m is the number of MQTL. A method is presented to reduce the number of equations per animal to one by combining information on all MQTL and polygenes into one numerator relationship matrix. It is illustrated how the method can accommodate individuals with partial or no marker information. Numerical examples are given to illustrate the methods presented. Opportunities to use the presented model in constructing genetic maps are discussed.

Animals↗
PubMed1996

The use of multiple markers in a Bayesian method for mapping quantitative trait loci.

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers. The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.

Algorithms↗
PubMed1997

Linkage mapping in experimental crosses: the robustness of single-gene models.

The robustness of parametric linkage mapping against model misspecification is considered in experimental breeding designs, with a focus on localization of the gene. By examining the expected LOD across the genome, it is shown that single-gene models are quite robust, even for polygenic traits. However, when the marker map is of low resolution, linked polygenes can give rise to an apparent "ghost" gene, mapped to an incorrect interval. The results apply equally well to quantitative traits or qualitative (categorical) traits. The results are derived for backcross populations, with a discussion of extensions to intercross populations and relative-pair mapping in humans.

Crosses, Genetic↗
PubMed1997

Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms.

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.

Algorithms↗
PubMed1999

Mutational adaptation of Escherichia coli to glucose limitation involves distinct evolutionary pathways in aerobic and oxygen-limited environments.

Mutational adaptations leading to improved glucose transport were followed with Escherichia coli K-12 growing in glucose-limited continuous cultures. When populations were oxygen limited as well as glucose limited, all bacteria within 280 generations contained mutations in a single codon of the ptsG gene. V12F and V12G replacements in the enzyme IIBC(Glc) component of the glucose phosphotransferase system were responsible for improved transport. In stark contrast, ptsG mutations were uncommon in fully aerobic glucose-limited cultures, in which polygenic mutations in mgl, mlc, and malT (regulating an alternate high-affinity Mgl/LamB uptake pathway) spread through the adapted population. Hence the same organism adapted to the same selection (glucose limitation) by different evolutionary pathways depending on a secondary environmental factor. The clonal diversity in the adapted populations was also significantly different. The PtsG V12F substitution under O(2) limitation contributed to a universal "winner clone" whereas polygenic, multiallelic changes led to considerable polymorphism in aerobic cultures. Why the difference in adaptive outcomes? E. coli physiology prevented scavenging by the LamB/Mgl system under O(2) limitation; hence, ptsG mutations provided the only adaptive pathway. But ptsG mutations in aerobic cultures are overtaken by mgl, mlc, and malT adaptations with better glucose-scavenging ability. Indeed, when an mglA::Tn10 mutant with an inactivated Mgl/LamB pathway was introduced into two independent aerobic chemostats, adaptation of the Mgl(-) strain involved the identical ptsG mutation found under O(2)-limited conditions with wild-type or Mgl(-) bacteria.

Adaptation, Physiological↗
PubMed1975

Genetic modification of recombination rate in Tribolium castaneum.

Asymmetrical responses were obtained in a replicated study of 15 generations of two-way selection for recombination rate between the ruby (rb) and jet (j) loci in Tribolium castaneum. Recombination rates in the two replicate high lines increased from an average of 0.22 in the base populations to an average of 0.42 at generation 15. Recombination rate pooled over the 15 generations of selection in each low line was significantly less than the control but there was no clear downward trend in response to selection for decreased recombination rate. The realized heritabilities were 0.16 +/- 0.03 and 0.17 +/- 0.02 in the two high lines, and were not significantly different from zero in the two low lines. Selection was based on crossing over in cis females only; however, rates measured in cis males after 12 generations showed the same response patterns as female rates. Similar response patterns were also determined for recombination measured in trans males and females at generation 18 following three generations of relaxed selection. The distribution of recombination rates measured in backcross beetles [(H X L) X H and (H X L) X L] at generation 12 indicated polygenic control with those genes decreasing recombination rate being dominant. Detailed analysis of recombination rates in F1's produced by interline crosses at generation 15 confirmed the directional dominance findings. Under a polygenic model of recombination modifiers in which low recombination is dominant to high, average recombination rates will increase as inbreeding progresses, thus providing a mechanism for the production of new gene combinations in small populations.

Animals↗
PubMed2004

Genetics of infectious diseases.

Infectious diseases represent a major health problem worldwide, both in terms of morbidity and mortality. A complex combination of environmental, pathogen and host genetic factors plays a role in determining both susceptibility to particular microbes and the course of infection. Numerous studies have now mapped and identified relevant genes using a variety of both family-based and population-based approaches. Much interest has been focused on susceptibility to malaria, HIV/AIDS and mycobacterial infection, but other bacterial, viral and parasitic diseases are receiving increasing attention. Some major genes have been identified by genome scans of multi-case families, and mouse genetics has contributed to mapping and identification of a few genes. However, the great majority of known susceptibility loci emerged from screening of likely candidate genes. The emerging picture is of highly polygenic diseases, with occasional major genes, along with significant inter-population heterogeneity. This genetic architecture likely reflects the role that evolutionary selection has played in generating and maintaining a diverse repertoire of susceptibility/resistance loci, most with individually small effects. Genome-wide association studies with large sample sizes will be required to define the majority of the relevant polygenes.

Animals↗
PubMed2005

Susceptibility genes for complex epilepsy.

Common idiopathic epilepsies are, clinically and genetically, a heterogeneous group of complex seizure disorders. Seizures arise from periodic neuronal hyperexcitability of unknown cause. The genetic component is mostly polygenic, where each susceptibility gene in any given individual is likely to represent a small component of the total heritability. Two susceptibility genes have been so far identified, where genetic variation is associated with experimentally demonstrated changes in ion channel properties, consistent with seizure susceptibility. Rare variants and a polymorphic allele of the T-type calcium channel CACNA1H and a polymorphic allele and a rare variant of the GABA(A) receptor delta subunit gene have differential functional effects. We speculate that these and other as yet undiscovered susceptibility genes for complex epilepsy could act as 'modifier' loci, affecting penetrance and expressivity of the mutations of large effect in those 'monogenic' epilepsies with simple inheritance that segregate through large families. Discovery of epilepsy-associated ion channel defects in these rare families has opened the door to the discovery of the first two susceptibility genes in epilepsies with complex genetics. The susceptibility genes so far detected are not commonly involved in complex epilepsy suggesting the likelihood of considerable underlying polygenic heterogeneity.

Alleles↗
PubMed1983

Extensions to multivariate normal models for pedigree analysis. II. Modeling the effect of shared environment in the analysis of variation in blood lead levels.

A multivariate normal model for pedigree analysis is applied to blood lead measurements from 617 individuals in 80 families in Melbourne, Australia, studied in 1977-1978. A new method is introduced for estimating time dependence of the family covariance matrix for blood lead levels; this time dependence can be interpreted as arising from the effects of common family environment on blood lead levels. Methods for the testing of assumptions and detection of outlying pedigrees and outlying individuals are applied. No correlation between blood lead levels of spouses was observed, but an effect of shared family environment was suggested by the difference between an estimated sibling correlation of about 0.5 for young sibling pairs living together and of about 0.1 for older siblings no longer living together. As there was no significant polygenic additive effect, the non-zero correlation between older siblings is more likely to be due to continuing effects of (environmental) factors shared in youth, rather than to a polygenic dominant effect. It is estimated that smoking 20 cigarettes per day is associated with an increase of about 12 per cent in blood lead level.

Adolescent↗
PubMed1987

Partitioning the variability of fasting plasma glucose levels in pedigrees. Genetic and environmental factors.

Fasting plasma glucose measurements made in 1972-1977 on normoglycemic individuals in three-generation Caucasian pedigrees from Rochester, Minnesota were analyzed. The authors determined the contributions of polygenic loci and environmental factors to fasting plasma glucose variability in these pedigrees. To that end, fasting plasma glucose measurements were normalized by an inverse normal scores transformation and then regressed separately for males and females on measured concomitants including age, body mass index (weight/height2), season of measurement, sex hormone use, and diuretic use. The authors found that 27.7% of the variability in normalized fasting plasma glucose in these pedigrees is explained by these measured concomitants. Subsequent variance components analysis suggested that unmeasured polygenic loci and unmeasured shared environmental factors together account for at least an additional 36.7% of the variability in normalized fasting plasma glucose, with genes alone accounting for at least 27.3%. These results are consistent with the known familiality of diabetes, for which fasting plasma glucose level is an important predictor. Further, these familial factors provide an explanation for at least half the variability in normalized fasting plasma glucose which remains after regression on known concomitants.

Adolescent↗
PubMed2004

Bayesian inference on major loci in related multigeneration selection lines of laying hens.

A mixed inheritance model, postulating a polygenic effect and differences between the 3 genotypes of a biallelic locus, was fitted separately to the data of 2 multigeneration selection lines and a control evolving from a common base population. Inferences about the model were drawn from the application of the Gibbs sampler. Body weight at 20 and 40 wk (BW20, BW40) and average egg weight to 40 wk (EW40) were included in the analyses. Significance of differences between posterior means of parameters was established by comparing their 95% highest probability density regions. Significant (P < 0.05) additive and dominance effects due to the genotypes at the major locus were found for all traits. The allele causing a lower trait value was the (partial) dominant one in all traits, leading to a negative dominance effect. The additive variance due to the major locus was also significant, i.e., greater than zero (P < 0.05) in all traits, whereas the dominance variance was only important for EW40. With the exception of the residual variances of one selection and the control line, no (P > 0.05) differences of posterior means of any parameter could be observed between lines. No significant genotypic or polygenic selection response was found for BW40. On the contrary, both genetic responses were found significant for EW40 in the selected lines, but not in the control. No differences (P > 0.05) between lines could be observed for the derived frequencies of the allele causing the higher trait value and the frequencies of one homozygote and the heterozygote genotypes at the major locus. The detection of a major locus with relatively modest effect confirmed that this type of analysis with data from selected lines was indeed powerful.

Animals↗
PubMed1989

The genetics of diabetes susceptibility in mice.

The factors associated with a diabetes-susceptible genotype in mice exhibiting various forms of heritable glucose intolerance syndromes are discussed. Genetic models of insulin-dependent and non-insulin-dependent diabetes in mice are described. Although single gene mutations can be defined for each model that are major contributors to diabetogenic stress, polygenic interactions are required for the expression of a diabetic phenotype, and environmental factors are also contributory. Several strongly penetrant single gene mutations are capable of affecting obesity and insulin-resistant states. Analysis of inbred strain genomic interactions with one of these recessive obesity-producing genes, diabetes (db), suggests that development of a diabetic phenotype is dependent on the strength of an interaction between the db gene and sulfotransferase enzymes. Specifically, diabetes-susceptible vs. resistant inbred strain backgrounds can be distinguished by the extent to which the db mutation elicits an accelerated sequestration by sulfoconjugation of tissue estrogens while androgens remain free. In a male gender- (and Y chromosome-)associated model of transient glucose intolerance, stress as well as a requirement for both adrenal and testicular secretions are each components of the susceptibility background. In the obesity-associated diabetes models, autoimmunity, when it occurs, is a secondary reflection of pancreatic beta cell destruction. The nonobese diabetic (NOD) mouse, in contrast, represents a model in which autoimmunity against beta cells is a primary event in the development of insulin-dependent diabetes. In NOD mice, a gene that is either the unique class II gene in the major histocompatibility complex or is in linkage disequilibrium with this complex makes a major (recessivelike) contribution to diabetes susceptibility. However, diabetogenesis can be mediated only through a multifactorial interaction among this susceptibility locus and multiple unlinked genetic loci regulating immune responsiveness. In addition, the NOD mouse represents one of the best models of diabetes available for demonstrating a critical interaction between heredity and environmental factors. The polygenic nature of the various heritable forms of glucose intolerance syndromes in mice points to a comparable or even greater genetic heterogeneity underlying the major types of diabetes in humans.

Animals↗