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Based on studies with natural populations, we offer a genetic model for sympatric speciation that could have broad application to polyphagous animals with habitat differences. The model comprises three steps, each of which includes simple genetic changes and plausible selective forces.
In this paper, we develop a new methodology to design synthetic genetic switch networks with multiple genes and time delays, by using monotone dynamical systems. We show that the networks with only positive feedback loops have no stable oscillation but stable equilibria whose stability is independent of the time delays. In other words, such systems have ideal properties for switch networks and can be designed without consideration of time delays, because the systems can be reduced from functional spaces to Euclidian spaces. Therefore, we can ensure that the designed switches function correctly even with uncertain delays. We first prove the basic properties of the genetic networks composed of only positive feedback loops, and then propose a procedure to design the switches, which drastically simplifies analysis of the switches and makes theoretical analysis and design tractable even for large-scaled systems. Finally, to demonstrate our theoretical results, we show biologically plausible examples by designing a synthetic genetic switch with experimentally well investigated lacI, tetR, and cI genes for numerical simulation.
The present paper examines a specific genetic model as a finite Markov process, using the normal matrix approach. This model is the two locus selfing model with selection studied by Tan (1973), who used an eigenvalue approach. The properties of the process are analytically and numerically investigated and the effects of selection and cross-over on the transition from a heterozygotic parent through several generations of heterozygotic progeny are assessed. These results enlarge upon Tan's work and, in addition, present two new aspects of the model. In particular (1) the expected number of generations of heterozygotic progeny of genotype j that will descend from a heterozygotic parent of genotype i and (2) the variance of this number of generations about the mean value have not been previously considered.
Although the left and right human cerebral hemispheres differ both functionally and anatomically, little is known about the environmental or genetic factors that govern central nervous system asymmetry. Nevertheless, cerebral asymmetry is strongly correlated with handedness, and handedness does have a significant genetic component. To explore the relative contribution of environmental and genetic influences on cerebral asymmetry, we examined the volumes of left and right cerebral cortex in a large cohort of aging identical and fraternal twins and explored their relationship to handedness. Cerebral lobar volumes had a major genetic component, indicating that genes play a large role in changes in brain volume that occur with aging. Shared environment, which likely represents in utero events, had about twice the effect on the left hemisphere as on the right, consistent with less genetic control over the left hemisphere. To test the major genetic models of handedness and cerebral asymmetry, twin pairs were divided into those with two right handers and those with at least one left hander (nonright handers). Genetic factors contributed twice the influence to left and right cerebral hemispheric volumes in right-handed twin pairs, suggesting a large decrement in genetic control of cerebral volumes in the nonright-handed twin pairs. This loss of genetic determination of the left and right cerebral hemispheres in the nonright-handed twin pairs is consistent with models postulating a right-hand/left-hemisphere-biasing genetic influence, a "right-shift" genotype that is lost in nonright handers, resulting in decreased cerebral asymmetry.
Parkinson's disease (PD) is a neurodegenerative disease characterized by a loss of dopaminergic neurons in the substantia nigra. There is a need for genetic animal models of PD for screening and in vivo testing of novel restorative therapeutic agents. Although current genetic models of PD produce behavioral impairment and nigrostriatal dysfunction, they do not reproduce the loss of midbrain dopaminergic neurons and 3,4-dihydroxyphenylalanine (L-DOPA) reversible behavioral deficits. Here, we demonstrate that Pitx3-deficient aphakia (ak) mice, which have been shown previously to exhibit a major loss of substantia nigra dopaminergic neurons, display motor deficits that are reversed by L-DOPA and evidence of "dopaminergic supersensitivity" in the striatum. Thus, ak mice represent a novel genetic model exhibiting useful characteristics to test the efficacy of symptomatic therapies for PD and to study the functional changes in the striatum after dopamine depletion and L-DOPA treatment.
This study is to explore the genetic model of type 2 diabetes mellitus (type 2 DM) among the hereditary family. One hundred and thirty-six pedigrees of familial type 2 DM were studied. The heritability of type 2 DM was estimated according to Falconer's method and the multi-factorial inheritance analyzed according to Penrose's method. Complex segregation analysis was performed using S.A.G.E-REGD. The heritability of familial type 2 DM was 94 07%-/+5.84%. Dominant major gene might influence the genesis of type 2 DM. Analysis of multi-factorial inheritance indicated that there be two genetic patterns respectively in male and female populations. By complex segregation analysis,environment,non-transmitted and co-dominant inheritance were rejected. Autosomal dominant (AD) inheritance and autosomal recessive (AR) inheritance was accepted but AR inheritance was the best pattern. This study suggested that type 2 DM had significant heritability and genetic heterogeneity,which appeared to be a disease of multi-factorial inheritance generally and autosomal dominant (AD) inheritance in part of pedigrees.
BACKGROUND AND PURPOSE: Hypertension is the most common risk factor for hemorrhagic stroke. An experimental model of stroke, the stroke-prone spontaneously hypertensive rat (SHRSP), which has been enormously useful in studies of cerebral circulation, has been used in >1000 papers. However, SHRSP usually have an ischemic or less commonly hemorrhagic stroke in the cortex, not in the brain stem, cerebellum, or basal ganglia, as in patients with hypertension. The goal of this study was to develop a model of hemorrhagic stroke in hypertensive mice. METHODS: A genetic model of hypertensive mice, double transgenic mice (R+/A+) that overexpress both human renin (R+) and human angiotensinogen (A+), and nonhypertensive control mice were divided into 3 groups: (1) high-salt diet; (2) Nomega-nitro-L-arginine methyl ester (L-NAME), an inhibitor of nitric oxide synthases, in drinking water; and (3) high-salt diet and L-NAME. RESULTS: All R+/A+ mice on high-salt diet and L-NAME died within 10 weeks, with hemorrhage in the brain stem, and several of the mice had hemorrhages in brain stem, cerebellum, and basal ganglia. No control mice on high-salt diet and L-NAME had hemorrhagic stroke. Arterial pressure in R+/A+ mice increased progressively during high-salt diet and L-NAME. In R+/A+ and control mice, high-salt diet or L-NAME alone did not increase arterial pressure. CONCLUSIONS: We now describe the first model of spontaneous hemorrhagic strokes in hypertensive mice. The type and locations of stroke are reasonably similar to those observed in patients with hypertension.
Linkage analysis of complex diseases raises a number of important methodological problems. One of them concerns the clinical classification of disease phenotypes. In this study, we investigate the effects of false positive misclassification on the estimation of the recombination fraction and on the power and the robustness of tests for linkage. These effects are investigated 1) when the genetic model of the trait locus is known; and 2) when it is unknown, by maximizing the likelihood of the marker configuration given the disease status in the family. Results show that linkage analysis of misclassified data leads to an overestimation of the recombination fraction and a loss of power of the linkage test. The results are quite similar in both situations. However, the linkage test itself is robust to this kind of misclassification error.
Although family studies have consistently reported elevated rates of schizophrenia among the relatives of schizophrenics, the exact nature of the transmission of the disorder remains uncertain. Genetic models hypothesized to explain the transmission of schizophrenia include the generalized single locus and multifactorial threshold models. Here we briefly describe these models and test their goodness-of-fit to a single data set on the pooled morbid risks of schizophrenia among the relatives of schizophrenic probands in nine different classes of relatives with five different degrees of genetic relatedness. The generalized single locus model is rejected, while a pure polygenic threshold model does fit the observed risks. Allowance for environmental sources of familial resemblance under the multifactorial threshold model significantly improved the fit of the model to the data. An application of the multifactorial model to family data on tuberculosis is also reported. For tuberculosis, a strong familial environmental but not genetic effect was found, consistent with the known infectious etiology of this condition, showing that the finding of a strong genetic effect upon schizophrenia is not a necessary bias of these methods of analysis. The implications of these results for the search for major gene effects in schizophrenia are discussed.
A small number of mammalian loci exhibit genomic imprinting, in which only one copy of a gene is expressed while the other is silenced. At some such loci, the maternally inherited allele is inactivated; others show paternal inactivation. Several hypotheses have been put forward to explain how this genetic system could have evolved in the face of the selective advantages of diploidy. In this study, we examine the variance-minimization hypothesis, which proposes that imprinting arose through selection for reduced variation in levels of gene expression. We present an evolutionary genetic model incorporating both this selection pressure and deleterious mutations to elucidate the conditions under which imprinting could evolve. Our analysis implies that additional mechanisms such as genetic drift are required for imprinting to evolve from an initial nonimprinting state. Other predictions of this hypothesis do not appear to fit the available data as well as predictions for two alternative hypotheses, genetic conflict and the ovarian time bomb. On the basis of this evidence, we conclude that the variance-minimization hypothesis appears less adequate to explain the evolution of genomic imprinting.
Programmed cell death or apoptosis is an important process to form normal adult cytoarchitecture. But in vivo analysis of neuronal apoptosis has not been well advanced. Therefore, apoptotic cell death of a particular neuronal system or anatomical part in a mutant is an invaluable target to learn about a link between a gene and neuronal apoptosis. Ataxia (ax) is an autosomal recessive neurological mutant mouse. We recently investigated brains of homozygotes for ataxia Jackson (ax(J)), an allele of ax, using TUNEL method. A few TUNEL-positive cells were observed in the granular cell layer of the cerebellum, the dentate gyrus, and the olfactory bulb of phenotypically normal littermates (ax(J)/+ or +/+) aged at 23-38 days. In affected ax(J)/ax(J) mice, however, the number of TUNEL-positive cells was significantly increased in the cerebellum, particularly in the granular cell layer (p < 0.05). The ax(J) mouse will be an in vivo unique model for studies on the genetic basis of apoptotic neuronal cell death, and identification of the ax gene is desired to elucidate molecular basis of the apoptosis.
Ataxia-telangiectasia (AT) is a multifaceted autosomal recessive disorder, inherited as a single gene in each family, presumably due to a defective DNA processing protein such as a recombinase, endonuclease or even a regulatory DNA-binding protein. We are attempting to identify the chromosomal location of the AT gene(s) by performing linkage analyses on a variety of genetic models. At least five AT complementation groups have been defined. This genetic heterogeneity complicates linkage analysis. Model I assumes that the complementation genes are clustered into a single genomic region and, therefore, lod scores of linkage data from all families can be added. Model II assumes that the AT complementation genes are dispersed throughout the genome and the lod scores cannot be added. This model necessitates assigning the complementation group of every family that is included in the linkage analyses and reduces the number of families in each data base. Model III utilizes heterozygote identification to follow the AT gene (in a Group A pedigree of 61 members) as a dominant trait, thereby increasing the amount of linkage information that can be derived from that family. Model IV will focus only on consanguineous offspring of first-cousin marriages, seeking to identify the location of the AT gene(s) by the increased degree of homozygosity of genetic markers in close proximity. This model has several advantages, including that much smaller numbers of patients are required. Model V assumes that a subset of our patients will carry deletions and can be used to confirm the relationship of a candidate gene to the AT phenotype. Progress: Models I and II have been used to survey 7% and 2% of the genome, respectively. (An additional 5% of the genome can be added for exclusion of the X chromosome on clinical grounds). Model III is intended to survey the entire genome. Our initial studies have surveyed approximately 30% of the genome. Several areas of increased lod scores have been identified and are under further investigation.
Genetic strategies for the post-genomic sequence age will be designed to provide information about gene function in a myriad of physiological processes. Here an ENU mutagenesis program (http://reprogenomics.jax.org) is described that is generating a large resource of mutant mouse models of infertility; male and female mutants with defects in a wide range of reproductive processes are being recovered. Identification of the genes responsible for these defects, and the pathways in which these genes function, will advance the fields of reproduction research and medicine. Importantly, this program has potential to reveal novel human contraceptive targets.
Statistical models were presented to estimate daily yields from either morning or evening test results. The 64,451 test-day records from 10,392 lactations of 8800 cows were available for analysis from experiments that were designed to investigate the accuracy of an alternate morning and evening four-weekly milk-testing scheme. The experiments were conducted in 152 herds from six German states and covered a span from 1994 to 1998. Milk yield, fat, and protein percentage were recorded for all of the morning and evening milkings. Seven statistical models were fitted to the data to derive formulas for estimating daily yields from morning or evening yields. In general, use of evening milkings less accurately estimated yields than did use of morning milkings. Among the three yield traits the lowest accuracy of estimation of daily yield was found for fat yield. Although the models do not differ much in the correlation between estimated and true daily yields, systematic under- and overestimation of daily yield at the beginning and end of lactation were observed in all models with the exception of model 6, which accounted for heterogeneous variances by parity class, milking interval class, and lactation stage by fitting separate regression formulas within each combination of the three factors. A study to validate the models showed that model 6 is also robust for the analyzed populations. Smoothing model 6 regression formulas across lactation stages caused a systematic pattern of estimation error, although loss in accuracy was minimal by fitting far fewer parameters in the regression formulas. Differences in the accuracy of alternate milking schemes to predict daily yields were found between traits, between morning and evening milkings, and between parity classes. Compared with true daily yields from different lactation stages, variances and correlations of the estimated yields were reduced, which must be accounted for in genetic evaluation. The use of estimated daily yields from morning or evening milkings has a smaller impact on estimated breeding values of bulls than cows. As a result of lower heritability and repeatability of estimated daily yields than true daily yields, the weight on own test-day records for estimating cows' breeding values is lower when cows are in a.m.-p.m. than conventional monthly testing schemes. However, the difference in the weights between estimated and true daily yields decreases as lactation progresses. Use of estimated daily yields is less reliable for estimating breeding value than use of true daily yields.
The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.
A condition is derived for reciprocal altruism to evolve by kin or group selection. It is assumed that many additively acting genes of small effect and the environment determine the probability that an individual is a reciprocal altruist, as opposed to being unconditionally selfish. The particular form of reciprocal altruism considered is TIT FOR TAT, a strategy that involves being altruistic on the first encounter with another individual and doing whatever the other did on the previous encounter in subsequent encounters with the same individual. Encounters are restricted to individuals of the same generation belonging to the same kin or breeding group, but first encounters occur at random within that group. The number of individuals with which an individual interacts is assumed to be the same within any kin or breeding group. There are 1 + i expected encounters between two interacting individuals. On any encounter, it is assumed that an individual who behaves altruistically suffers a cost in personal fitness proportional to c while improving his partner's fitness by the same proportion of b. Then, the condition for kin or group selection to prevail is [Formula: see text] if group size is sufficiently large and the group mean and the within-group genotypic variance of the trait value (i.e., the probability of being a TIT-FOR-TAT strategist) are uncorrelated. Here, C, Vb, and Tb are the population mean, between-group variance, and between-group third central moment of the trait value and r is the correlation between the additive genotypic values of interacting kin or of individuals within the same breeding group. The right-hand side of the above inequality is monotone decreasing in C if we hold Tb/Vb constant, and kin and group selection become superfluous beyond a certain threshold value of C. The effect of finite group size is also considered in a kin-selection model.
The self-assembly characteristics of the model genetically engineered elastin-like polymer [(VPGVG)2(VPGEG)(VPGVG)2]15 have been studied in this work. An AFM study of the topology of polymer films deposited from acid and basic solutions on a hydrophobic silicon substrate has been carried out. Under acidic conditions, polymer deposition results in a flat surface with no particular topological features. However, from basic solutions, polymer deposition clearly shows an aperiodic pattern of nanopores ( approximately 70 nm width and separated about 150 nm). This dramatic dependence of film topology on pH is explained in terms of the different polarity of the free gamma-carboxyl group of the glutamic acid. In the carboxylate form, this moiety shows a markedly higher polarity than the rest of the polymer domains and the substrate itself. Under these conditions, the charged carboxylates impede hydrophobic contact with their surroundings, which is the predominant assembly pathway for this type of polymer. The charged domains, along with their hydration sphere, are then segregated from the hydrophobic surroundings giving rise to nanopores.
In spite of many advances in monitoring oxygenation and preventing cerebro-vascular accidents, there is still considerable morbidity and mortality from conditions with cerebral blood flow impairment and O2 deprivation leading to hypoxic/ischemic brain injury. Part of this failure is related to the complexity of the cascade of events that ensue after hypoxia or ischemia, but also part of it may be related to the fact that most research in the previous few decades has focused, justifiably, on cerebral vessel disease. However, an important aspect of the cascade is dependent on many factors that are inherent to the nature and response of the tissue itself. Hence, there is more need now for a two-pronged approach to hypoxic/ischemic brain injury, one focusing on vessel disease, its prevention, and treatment, and the other centering on the brain tissue itself and the factors that render neurons and glia more susceptible or more tolerant to a lack of oxygenation. In the past several years, a number of methods, techniques, and animal models have been used to address the response of neurons and glia to lack of oxygen. In this review, we highlight some novel ideas and some results that we and others have obtained, mostly pertaining to the genetic endowment and responses of the central nervous system to O2 deprivation. The role and importance of genetic models, such as the Drosophila melanogaster, are discussed, and an example illustrating how to harness the power of Drosophila genetics is detailed.