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.     

随机SNP在全基因组关联研究人群分层分析中的应用

在复杂疾病的全基因组关联研究中,人群分层现象会增加结果的假阳性率,因此考虑人群遗传结构、控制人群分层是很有必要的。而在人群分层研究中,使用随机选择的SNP的效果还有待进一步探讨。文章利用HapMap Phase2人群中无关个体的Affymetrix SNP 6.0芯片分型数据,在全基因组上随机均匀选择不同数量的SNP,同时利用f值和Fisher精确检验方法筛选祖先信息标记（Ancestry Informative Markers,AIMs）。然后利用HapMap Phase3中的无关个体的数据,以F-statistics和STRUCTURE分析两种方法评估所选出的不同SNP组合对人群的区分效果。研究发现,随机均匀分布于全基因组的SNP可用于识别人群内部存在的遗传结构。文章进一步提示,在全基因组关联研究中,当没有针对特定人群的AIMs时,可在全基因组上随机选择3000以上均匀分布的SNP来控制人群分层。     

人类复杂疾病关联研究中群体分层的检出和校正

病例对照研究是鉴定多基因疾病易感位点重要的遗传流行病学方法, 而群体分层是导致病例对照研究关联研究结果出现偏倚甚至是假关联的重要原因之一。文章对人群分层的检出及校正的方法和原理进行了阐述, 包括基于核心家系的传递/不平衡检验(TDT)以及基于不相关基因组遗传标记的基因组对照(GC)和结构化关联(SA)等, 并且对这几种方法进行了比较。     

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.     

Control of population stratification by correlation-selected principal components

In genome-wide association studies, population stratification is recognized as producing inflated type I error due to the inflation of test statistics. Principal component-based methods applied to genotypes provide information about population structure, and have been widely used to control for stratification. Here we explore the precise relationship between genotype principal components and inflation of association test statistics, thereby drawing a connection between principal component-based stratification control and the alternative approach of genomic control. Our results provide an inherent justification for the use of principal components, but call into question the popular practice of selecting principal components based on significance of eigenvalues alone. We propose a new approach, called EigenCorr, which selects principal components based on both their eigenvalues and their correlation with the (disease) phenotype. Our approach tends to select fewer principal components for stratification control than does testing of eigenvalues alone, providing substantial computational savings and improvements in power. Analyses of simulated and real data demonstrate the usefulness of the proposed approach.     

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.     

Argentine population genetic structure: large variance in Amerindian contribution

Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies.     

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.     

No signature of Y chromosomal resemblance between possible descendants of the Cimbri in Denmark and Northern Italy

Two European populations are believed to be related to the ancient Germanic tribe Cimbri: one living in Northern Italy, the other living in Jutland, Denmark. The people called Cimbri are documented in the ancient Roman historical record. Arriving from the far north their movements can be tracked from successive battles with the Romans. The Cimbri finally entered Italy from the northeast and were defeated at Vercellae (present day Vercelli) in 101 BC by Gaius Marius and his professional legions. Classical sources from the first centuries AD relate the homeland of the Cimbri to the coasts around the Elb estuary (northern Germany) or specifically towards the north (Himmerland in northern Jutland). In the alpine parts of Veneto, northeast of the historical battlefield, local traditions dating back to late medieval time, identify a local population as Cimbri living in Terra dei Cimbri. They are considered the descendents of the Germanic combatants that fled the battlefield at Vercelli. As the defeated Cimbri that possibly fled to the mountains of Northern Italy most likely would have been male (warriors), the present study investigated the possible Y chromosomal diversity of the two present populations using microsatellite markers and single nucleotide polymorphisms. While Cimbri from Himmerland resembled their geographical neighbors from Denmark for the Y-chromosome markers, Cimbri from Italy were significantly differentiated both from Cimbri from Himmerland and from Danes. Therefore, we were not able to show any biological relationship for uniparentally transmitted markers.     

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.     

A climatic stratification of the environment of Europe

Aim To produce a statistical stratification of the European environment, suitable for stratified random sampling of ecological resources, the selection of sites for representative studies across the continent, and to provide strata for modelling exercises and reporting. Location A ‘Greater European Window’ with the following boundaries: 11° W, 32° E, 34° N, 72° N. Methods Twenty of the most relevant available environmental variables were selected, based on experience from previous studies. Principal components analysis (PCA) was used to explain 88% of the variation into three dimensions, which were subsequently clustered using an ISODATA clustering routine. The mean first principal component values of the classification variables were used to aggregate the strata into Environmental Zones and to provide a basis for consistent nomenclature. Results The Environmental Stratification of Europe (EnS) consists of 84 strata, which have been aggregated into 13 Environmental Zones. The stratification has a 1 km² resolution. Aggregations of the strata have been compared to other European classifications using the Kappa statistic, and show ‘good’ comparisons. The individual strata have been described using data from available environmental databases. The EnS is available for noncommercial use by applying to the corresponding author. Main conclusions The Environmental Stratification of Europe has been constructed using tried and tested statistical procedures. It forms an appropriate stratification for stratified random sampling of ecological resources, the selection of sites for representative studies across the continent and for the provision of strata for modelling exercises and reporting at the European scale.     

Molecular genetic studies in Saudi population; identified variants from GWAS and meta-analysis in stroke

IntroductionStroke is a multifactorial and heterogeneous disorder, correlates with heritability and considered as one of the major diseases. The prior reports performed the variable models such as genome-wide association studies (GWAS), replication, case-control, cross-sectional and meta-analysis studies and still, we lack diagnostic marker in the global world. There are limited studies were carried out in Saudi population, and we aim to investigate the molecular association of single nucleotide polymorphisms (SNPs) identified through GWAS and meta-analysis studies in stroke patients in the Saudi population.MethodsIn this case-control study, we have opted gender equality of 207 cases and 207 controls from the capital city of Saudi Arabia in King Saud University Hospital. The peripheral blood (5 ml) sample will be collected in two different vacutainers, and three mL of the coagulated blood will be used for lipid analysis (biochemical tests) and two mL will be used for DNA analysis (molecular tests). Genomic DNA will be extracted with the collected blood samples, and specific primers will be designed for the opted SNPs (SORT1-rs646218 and OLR1-rs11053646 polymorphisms) and PCR-RFLP will be performed and randomly DNA sequencing will be carried out to cross check the results.ResultsThe rs646218 and rs11053646 polymorphisms were significantly associated with allele, genotype and dominant models with and without crude odds ratios (OR’s) and Multiple logistic regression analysis (p < 0.05). Correlation between lipid profile and genotypes has confirmed the significant relation between triglycerides and rs646218 and rs1105364 6polymorphisms. However, rs11053646 polymorphism was correlated with HDLC (p = 0.04). Genotypes were examined in both males' vs. males and females' vs. females in cases and control and we concluded that in rs11053646 polymorphisms with male subjects compared between cases and controls found to be associated with dominant model heterozygote genotypes (p < 0.05).ConclusionThe results of the current study confirmed the SORT1 and OLR1 SNPs were associated in the Saudi population. The current results were in the association with the prior study results documented through GWAS and meta-analysis association. However, other ethnic population studies should be performed to rule out in the human hereditary diseases.     

Covariance between relatives in multibreed populations: additive model

Covariance between relatives in a multibreed population was derived for an additive model with multiple unlinked loci. An efficient algorithm to compute the inverse of the additive genetic covariance matrix is given. For an additive model, the variance for a crossbred individual is a function of the additive variances for the pure breeds, the covariance between parents, and segregation variances. Provided that the variance of a crossbred individual is computed as presented here, the covariance between crossbred relatives can be computed using formulae for purebred populations. For additive traits the inverse of the genotypic covariance matrix given here can be used both to obtain genetic evaluations by best linear unbiased prediction and to estimate genetic parameters by maximum likelihood in multibreed populations. For nonadditive traits, the procedure currently used to analyze multibreed data can be improved using the theory presented here to compute additive covariances together with a suitable approximation for nonadditive covariances.Supported in part by the Illinois Agricultural Experiment Station, Hatch Projects 35-0345 (RLF) and 35-0367 (MG)     

Forecasting the obesity epidemic in the aging U.S. population

Objective: The objective was to forecast BMI distribution in the U.S. population along with demographic changes based on past race‐, sex‐, and birth cohort‐specific secular trends. Research Methods and Procedures: We compiled data from 44,184 subjects from 4 National Health and Nutrition Examination Surveys (NHANES; 1971 to 2004). By race and sex, we fit regression models to create smoothed mean BMI curves by age for 1970 to 2010. Linking corresponding birth cohorts across age‐ and year‐specific mean BMI projections, we estimated the trajectory of relative BMI throughout each cohort's lifetime. These projections were validated using actual cohorts in the Nurses’ Health Study and Health Professionals Follow‐up Study. Combined with U.S. census, we predicted BMI distributions in 2010 and examined the joint impact of the obesity epidemic and population aging. Results: BMI secular trends in the past 3 decades differ significantly by birth cohort, sex, and race. If these trends continue, the prevalence of obesity is expected to reach 35%, 36%, 33%, and 55% in 2010 among white men, white women, black men, and black women, respectively, far from the Healthy People 2010 goal of 15%. Such forecasts translate into 9.3 million more obese adults 20 to 74 years of age than in 2000, 8.3 million of whom would be 50 years of age or older, and 8.5 million of whom would be white. The mean age among obese men and women is also expected to rise from 47 to 49 years among whites and from 43 to 44 years among blacks. Discussion: As the baby boom generation approaches retirement age, the continuing obesity epidemic signals a likely expansion in the population with obesity‐related comorbidities. A framework to combine BMI and demographic trends is essential in evaluating the burden and disparity associated with the epidemic in the aging U.S. population.     

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.     

An empirical approach to the analysis of forest stratification

Natural forest communities are made up of different overlapping elementary subpopulations consisting of individuals of different species and ages. To stratify the individuals of a forest stand into elementary subpopulations by using tree height records, a graphical method was empirically proposed employing a derivative of Pearson's type VII distribution as a basis. Arranging all of the individual trees in a stand in the descending order of their height (x), and introducing the rank (N) of any individual in the ordered ranking ofx, finite difference (n) ofN and three values ofx, i.e.,x(N), x(N−n), andx(N+n) labelled byN, N−n, andN+n, respectively, the proposed method used the linear relation betweenx(N) and [x(N−n)+x(N+n)]. On thex(N) vs.[x(N−n)+x(N+n)] diagram, the relation between both the variables could be approximated by a few segmental linear relations and used for stratifying the individuals of a forest stand into subpopulations. The method was applied for analyzing the vertical stratification in forest stands of different forest formations in Japan, Southeast Asia, Africa, and South America. The conclusions on stratification which resulted from the proposed method corresponded well to the conclusions on stratification from profile diagrams.     

A note on the nutrition of Rhodella

Rhodella maculata Evans has been grown in axenic culture. The alga is euryhaline but will not grow in acid conditions. It requires an exogenous source of vitamin B₁₂, is unable to grow in the dark on acetate or glucose and has a limited capability for utilising organic nitrogen sources.