Investigating population stratification and admixture using eigenanalysis of dense genotypes

Principal components analysis of genetic data is used to avoid inflation in type I error rates in association testing due to population stratification by covariate adjustment using the top eigenvectors and to estimate cluster or group membership independent of self-reported or ethnic identities. Eigendecomposition transforms correlated variables into an equal number of uncorrelated variables. Numerous stopping rules have been developed to identify which principal components should be retained. Recent developments in random matrix theory have led to a formal hypothesis test of the top eigenvalue, providing another way to achieve dimension reduction. In this study, I compare Velicer's minimum average partial test to a test on the basis of Tracy-Widom distribution as implemented in EIGENSOFT, the most widely used implementation of principal components analysis in genome-wide association analysis. By computer simulation of vicariance on the basis of coalescent theory, EIGENSOFT systematically overestimates the number of significant principal components. Furthermore, this overestimation is larger for samples of admixed individuals than for samples of unadmixed individuals. Overestimating the number of significant principal components can potentially lead to a loss of power in association testing by adjusting for unnecessary covariates and may lead to incorrect inferences about group differentiation. Velicer's minimum average partial test is shown to have both smaller bias and smaller variance, often with a mean squared error of 0, in estimating the number of principal components to retain. Velicer's minimum average partial test is implemented in R code and is suitable for genome-wide genotype data with or without population labels.     

A note on persistence about structured population models

In this paper, we report some results on persistence in two structured population models: a chronic- age-structured epidemic model and an age-duration-structured epidemic model. Regarding these models, we observe that the system is uniformly strongly persistent, which means, roughly speaking, that the proportion of infected subpopulation is bounded away from 0 and the bound does not depend on the initial data after a sufficient long time, if the basic reproduction ratio is larger than one. We derive this by adopting Thieme's technique, which requires some conditions about positivity and compactness. Although the compactness condition is rather difficult to show in general infinite-dimensional function spaces, we can apply Fréchet–Kolmogorov L ¹-compactness criteria to our models. The two examples that we study illuminate a useful method to show persistence in structured population models.     

A note on the population genetic consequences of delayed larval development in insects

Observations by Dobzhansky’s group in the 1940s suggesting that the presence of recessive genotypes could account for lower larval developmental rates in Drosophila melanogaster were not confirmed at the time and all subsequent investigations on this subject focused on the analysis of ecological models based on competition among pre-adult individuals. However, a paper published in this journal in 1991 eventually confirmed the finding made by Dobzhansky and his co-workers. In this report, we provide a theoretical analysis of the population genetic effects of a delay in the rate of larval development produced by such a genetic mechanism.     

SARS-CoV-2 associated COVID-19 in geriatric population: A brief narrative review

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has emerged as a fatal pandemic and has crushed even the world’s best healthcare systems. Globally, it has affected 40,373,228 individuals and resulted in 1,119,568 deaths as of October 19, 2020. Research studies have demonstrated that geriatric population is vastly vulnerable to COVID-19 morbidity and mortality given their age and preexisting chronic comorbidities such as cardiovascular disease, hypertension, diabetes mellitus, chronic pulmonary and chronic kidney disease The data regarding susceptibility of elderly population to COVID-19 is accruing and suggests that factors like age, gender, chronic comorbidity, inflammaging, immunosenescence and renin angiotensin system may be the contributing risk factors towards COVID-19 and associated mortality in elderly population. Based on updated scientific literature, this narrative review précises the clinical presentations and underlying risk factors that might be associated with COVID-19 morbidity in geriatric population and provides informed insights, and discusses clinical presentation, psychosocial impact, mortality and potential corticosteroid treatment and prevention strategies of COVID-19 in older adults.     

A brief note on growth physiology of plants

The concepts of physiological structure of plant axial organ and its main components are discussed. Their physiological meanings, in particular the role of the surface and the xylem proton pumps are highlighted: the former loosens the cell wall via acidification, and the latter produces the driving force for active uptake of water. Theoretical and experimental examination on the validity of the Lock-hart growth equation is reviewed. Development of a new experimental system, perfusible glycerinated hollow cylinder of cowpea hypocotyl, demonstrates the validity of the Lock-hart type mechanical equation even in such anin vitro system. The pH-dependency of both extensibility and yield threshold offer a strong support for the acid growth theory. A molecular model of cell wall extension is proposed on the basis of these results. The importance of growth regulation via control of the cell wall yield threshold is demonstrated as a very economical way, by an analogy with the performance of electron tube of triode type. Also augmentation of the classic acid growth theory is proposed on the basis of Katou's diagram and the Katou-Furumoto's model of active water uptake.     

How to separate genetic and environmental causes of similarity between relatives

Related individuals often have similar phenotypes, but this similarity may be due to the effects of shared environments as much as to the effects of shared genes. We consider here alternative approaches to separating the relative contributions of these two sources to phenotypic covariances, comparing experimental approaches such as cross-fostering, traditional statistical techniques and more complex statistical models, specifically the 'animal model'. Using both simulation studies and empirical data from wild populations, we demonstrate the ability of the animal model to reduce bias due to shared environment effects such as maternal or brood effects, especially where pedigrees contain multiple generations and immigration rates are low. However, where common environment effects are strong, a combination of both cross-fostering and an animal model provides the best way to avoid bias. We illustrate ways of partitioning phenotypic variance into components of additive genetic, maternal genetic, maternal environment, common environment, permanent environment and temporal effects, but also show how substantial confounding between these different effects may occur. Whilst the flexibility of the mixed model approach is extremely useful for incorporating the spatial, temporal and social heterogeneity typical of natural populations, the advantages will inevitably be restricted by the quality of pedigree information and care needs to be taken in specifying models that are appropriate to the data.     

Overview of techniques to account for confounding due to population stratification and cryptic relatedness in genomic data association analyses

Population-based genomic association analyses are more powerful than within-family analyses. However, population stratification (unknown or ignored origin of individuals from multiple source populations) and cryptic relatedness (unknown or ignored covariance between individuals because of their relatedness) are confounding factors in population-based genomic association analyses, which inflate the false-positive rate. As a consequence, false association signals may arise in genomic data association analyses for reasons other than true association between the tested genomic factor (marker genotype, gene or protein expression) and the study phenotype. It is therefore important to correct or account for these confounders in population-based genomic data association analyses. The common correction techniques for population stratification and cryptic relatedness problems are presented here in the phenotype–marker association analysis context, and comments on their suitability for other types of genomic association analyses (for example, phenotype–expression association) are also provided. Even though many of these techniques have originally been developed in the context of human genetics, most of them are also applicable to model organisms and breeding populations.     

水体热分层对万峰湖水环境的影响

2009年9月(秋季)和2010年1月(冬季)对南盘江流域峡谷型水库--万峰湖的水温和水化学(DO、pH、总磷)进行监测,结果表明:万峰湖水体在秋、冬季节均存在明显分层,秋季.水体分为3层,0～10 m为混匀层,10～50 m为斜温层,50 m以下为滞水层,这种温度分层阻止了水的对流混合,引起显著的水化学分层,形成底部厌氧层.冬季,水温下降,在水下50 m左右分层,表层随深度增加水温下降,下层为滞水层,水温较为均匀.相关性分析表明,万峰湖在2009年9月(秋季)和2010年1月(冬季)水温和DO、pH、总磷之间均为极显著相关,水化学分层与温度分层同步.     

Covariance between relatives for X-chromosomal loci in a population in disequilibrium

Summary According to Hardy-Weinberg, for a single autosomal locus, a population achieves equilibrium in one generation of random mating if allelic frequency is the same in the sexes, or in two generations if the frequency is not. For a single X-chromosomal locus, however, the approach to equilibrium oscillates and is gradual. Covariances between relatives for autosomal and for X-chromosomal loci are in the literature for a random mating population in equilibrium. Although assumption of equilibrium is defensible for an autosomal locus, it is less defensible for an X-chromosomal locus. Covariances between collateral and between lineal relatives are derived for X-chromosomal loci in a random mating population not in equilibrium. Collateral relatives such as sibs are of the same generation, and lineal relatives such as parent-offspring are of different generations. Coefficient of co-ancestry between relatives, based on identity by descent, was used in this development. Results are applicable to crossbreeding in livestock and poultry, and also to haplo-diploid organisms, such as the honeybee, in which the entire genome is equivalent to being X-chromosomal.Supported in part by the Illinois Agricultural Experiment Station, Hatch Project 35-0367     

Vertical movements of the surface water and thermal stratification in Rutland Water

Vertical movements of the water surface in Rutland Water were examined using water level gauges. The timing and extent of the surface seiches and slopes due to wind-stress were not well correlated with wind speed and direction; this is thought to be due to the complex shape of the reservoir. Unexplainable diel oscillations of the water surface occurred, and an examination of the thermal stratification showed the presence of upwelling and downwelling.     

A note on the relevance of human population genetic variation and molecular epidemiology to assessing radiation health risk for space travellers

We discuss the relevance to space medicine of studies concerning human genetic variation and consequent variable disease susceptibility or sensitivity between individuals. The size of astronaut and cosmonaut populations is both presently and cumulatively small, and despite the launch of the International Space Station, unlikely to increase by orders of magnitude within the foreseeable future. In addition, astronauts–cosmonauts constitute unrepresentative samples of their national populations. While the context of exposure for the astronaut–cosmonaut group is one unlikely to be replicated elsewhere than in space, aspects of specific exposures may be simulated by events such as occupational radiation exposure or radiation therapy. Hence, population-based studies of genetic susceptibility or sensitivity to disease, especially where it is precipitated by events that may simulate consequences of the space environment, likely will prove of value in assessing long-term health risks.     

The relationship between parental genetic or phenotypic divergence and progeny variation in the maize nested association mapping population

Appropriate selection of parents for the development of mapping populations is pivotal to maximizing the power of quantitative trait loci detection. Trait genotypic variation within a family is indicative of the family's informativeness for genetic studies. Accurate prediction of the most useful parental combinations within a species would help guide quantitative genetics studies. We tested the reliability of genotypic and phenotypic distance estimators between pairs of maize inbred lines to predict genotypic variation for quantitative traits within families derived from biparental crosses. We developed 25 families composed of ~200 random recombinant inbred lines each from crosses between a common reference parent inbred, B73, and 25 diverse maize inbreds. Parents and families were evaluated for 19 quantitative traits across up to 11 environments. Genetic distances (GDs) among parents were estimated with 44 simple sequence repeat and 2303 single-nucleotide polymorphism markers. GDs among parents had no predictive value for progeny variation, which is most likely due to the choice of neutral markers. In contrast, we observed for about half of the traits measured a positive correlation between phenotypic parental distances and within-family genetic variance estimates. Consequently, the choice of promising segregating populations can be based on selecting phenotypically diverse parents. These results are congruent with models of genetic architecture that posit numerous genes affecting quantitative traits, each segregating for allelic series, with dispersal of allelic effects across diverse genetic material. This architecture, common to many quantitative traits in maize, limits the predictive value of parental genotypic or phenotypic values on progeny variance.     

Thermal stratification and the stability of meromixis in the Pretoria Salt Pan,South Africa

The Pretoria Salt Pan, South Africa, a small (0.076 km²), shallow (Z_max = 2.85 m), hypersaline, maar lake, lies within a clearly-defined crater and is fed by a perennial, slightly saline (3 g l^-1) artesian spring. The lake has two distinct solar-heated peaks in its temperature profile, each of these peaks located in a highly turbid (>80 JTU) layer below a steep chemocline. The upper thermal peak, located at a depth of 10 cm, was transient, with a distinct diel pattern of diurnal heating and nocturnal cooling. The lower thermal peak, located below a steep chemocline and centred at approximately 60 cm, was stable and showed a seasonal pattern of winter heating (maximum: 38.5°C) and summer cooling (minimum: 27.4°C). The unusual bathymetry of the lake, combined with the sheltering effect of the crater rim and steep salinity gradient between the surface (30–80 g l^-1) and bottom water (280–310 g l^-1) prevented windmixing of surface waters beyond a depth of approximately 50 cm. During a 28 month study all water deeper than 55 cm remained anaerobic, and the lake appeared to be meromictic.     

A note on stability of discrete population models

P. Cull (1981) and G. Rosencranz (1983) studied a discrete population model described by the first-order difference equation xt+1 = g(xt) and obtained an important result on the global stability of the equilibrium point means when g(x) has only one extreme point (a maximum) in (0, means). Motivated by work of M. Kot and W. M. Schaffer (1984), a more general case is considered in which g(x) can have more then one maximum point in (0, means), and results on global stability are obtained. These results are applied to develop tests for global stability of the equilibrium point that imply other results in the literature on global stability.     

Covariances of relatives and selection response in generations of selfing from an outcrossed base population

Summary The covariances of relatives arising under selfing from a general outbred base population in linkage equilibrium and without epistasis given by Cockerham (1983) are expressed in an alternative form which is an extension of the treatment by Mather and Jinks (1982) of the more restricted population descended from a single F₁ family. Whereas no more than two quadratic components are required to describe any covariance in the case of F₁, descendants, this more general case calls for a total of four, three of which are needed for any particular covariance. The estimation of covariances and their use for the prediction of selection response is described for breeding programs initiated by one or more cycles of intermating among a number of parental lines, as advocated by Hansel (1964) and Jensen (1970). It is pointed out that the homozygous lines descended from such a population will have up to twice as much variance as those from an F₁ between a randomly chosen pair from the same population of parents. The selection method is especially recommended for undeveloped species in which the parental lines are not well characterized and large selection responses are needed.     

A preliminary study of changes in forest stratification along environmental gradients in Southeast Asia

Changes in forest stratification along environmental gradients in Southeast Asian forests were studied, by applying Quantification Method I to the records of tree height inventories and environmental conditions in 29 study forest stands. To stratify individual trees into subpopulations in a stand, an empirical and graphical method was used. After stratifying all the component individuals of the stand into subpopulations, the number of subpopulations per stand and mean tree height per subpopulation were calculated and adopted as indices of forest stratification. Of the two indices, the latter index changed linearly with respect to the maximum tree height in the stand. Hence, the number of subpopulations and the maximum tree height as a substitute for mean tree height per subpopulation were biotic dependent variables in the application of Quantification Method I, while abiotic independent variables were the following six categorized environmental factors: the number of wet months with over 100 mm month⁻¹ rainfall in a year, occurrence of fog, mean annual temperature, magnesium accumulation in mineral soil, soil water drainage, and forest fire. It was concluded that these biotic and abiotic variables were the components of multivariate regression models, which successfully explained the development of forest stratification in terms of habitat conditions.