The Impact of Population Demography and Selection on the Genetic Architecture of Complex Traits

Population genetic studies have found evidence for dramatic population growth in recent human history. It is unclear how this recent population growth, combined with the effects of negative natural selection, has affected patterns of deleterious variation, as well as the number, frequency, and effect sizes of mutations that contribute risk to complex traits. Because researchers are performing exome sequencing studies aimed at uncovering the role of low-frequency variants in the risk of complex traits, this topic is of critical importance. Here I use simulations under population genetic models where a proportion of the heritability of the trait is accounted for by mutations in a subset of the exome. I show that recent population growth increases the proportion of nonsynonymous variants segregating in the population, but does not affect the genetic load relative to a population that did not expand. Under a model where a mutation''s effect on a trait is correlated with its effect on fitness, rare variants explain a greater portion of the additive genetic variance of the trait in a population that has recently expanded than in a population that did not recently expand. Further, when using a single-marker test, for a given false-positive rate and sample size, recent population growth decreases the expected number of significant associations with the trait relative to the number detected in a population that did not expand. However, in a model where there is no correlation between a mutation''s effect on fitness and the effect on the trait, common variants account for much of the additive genetic variance, regardless of demography. Moreover, here demography does not affect the number of significant associations detected. These findings suggest recent population history may be an important factor influencing the power of association tests and in accounting for the missing heritability of certain complex traits.     

The Impact of Genetic Architecture on Genome-Wide Evaluation Methods

The rapid increase in high-throughput single-nucleotide polymorphism data has led to a great interest in applying genome-wide evaluation methods to identify an individual''s genetic merit. Genome-wide evaluation combines statistical methods with genomic data to predict genetic values for complex traits. Considerable uncertainty currently exists in determining which genome-wide evaluation method is the most appropriate. We hypothesize that genome-wide methods deal differently with the genetic architecture of quantitative traits and genomes. A genomic linear method (GBLUP), and a genomic nonlinear Bayesian variable selection method (BayesB) are compared using stochastic simulation across three effective population sizes and a wide range of numbers of quantitative trait loci (N_QTL). GBLUP had a constant accuracy, for a given heritability and sample size, regardless of N_QTL. BayesB had a higher accuracy than GBLUP when N_QTL was low, but this advantage diminished as N_QTL increased and when N_QTL became large, GBLUP slightly outperformed BayesB. In addition, deterministic equations are extended to predict the accuracy of both methods and to estimate the number of independent chromosome segments (M_e) and N_QTL. The predictions of accuracy and estimates of M_e and N_QTL were generally in good agreement with results from simulated data. We conclude that the relative accuracy of GBLUP and BayesB for a given number of records and heritability are highly dependent on M_e, which is a property of the target genome, as well as the architecture of the trait (N_QTL).THE rapid progress and reducing costs of genome sequencing and high-throughput DNA techniques have led to a great interest in applying genome-wide evaluation methods to identify individuals of high genetic merit. Genome-wide evaluation uses associations of a large number of SNP (single nucleotide polymorphism) markers across the whole genome with phenotypes to produce accurate estimates of breeding values (EBVs) for candidates to selection (Meuwissen et al. 2001). The accuracy of genome-wide selection (i.e., selection based on genomic EBVs) is expected to be substantially higher than that of traditional best linear unbiased prediction (BLUP) selection, which is based on pedigree and phenotypic data (Daetwyler et al. 2008; Goddard 2009; Hayes et al. 2009c). In addition, genome-wide selection has the potential to reduce inbreeding rates because of the increased emphasis on own rather than family information (Woolliams et al. 2002; Daetwyler et al. 2007; Dekkers 2007). Furthermore, the application of genome-wide evaluation approaches can significantly aid our understanding of quantitative trait genetic architecture.The genome-wide evaluation methods suggested to date can be broadly categorized into groups according to whether there is an assortment of the SNP by magnitude of effect or contribution to the variance. One group treats SNP homogeneously and includes variants of genomic best linear unbiased prediction (GBLUP). This group includes a form of ridge regression (Meuwissen et al. 2001) and the use of a realized relationship matrix computed from the markers instead of the traditional pedigree matrix (NejatiJavaremi et al. 1997; Villanueva et al. 2005; Hayes et al. 2009c). Both approaches have been shown to be equivalent (Habier et al. 2007; Goddard 2009). A second group provides for heterogeneity among SNP contributions to the variance, with some contributions permitted to be large while the remainder are small, possibly zero. This assortment is helped by Bayesian approaches, which place priors on numbers of SNP with major contributions (e.g., BayesA and BayesB; see Meuwissen et al. 2001, 2009; Lee et al. 2008), or with some penalty based on functions of the magnitude of effect for each SNP (e.g., Lasso; see Tibshirani 1996; Yi and Xu 2008) or with other smoothing metrics (Long et al. 2007). A third group attempts to reduce dimensionality by using principal components or partial least squares (Raadsma et al. 2008; Solberg et al. 2009) to identify an informative subset of SNP genotypes. The main two methods currently used in real data sets are a linear prediction method, GBLUP, and variants of nonlinear Bayesian variable selection approaches such as BayesB.In most simulated published data, the accuracy of BayesB outperformed that of GBLUP (e.g., Meuwissen et al. 2001; Habier et al. 2007; Lund et al. 2009). However, real data results have not consistently supported this conclusion. Two reviews of empirical results in dairy cattle to date have shown that GBLUP and BayesB result in very similar accuracies for most traits (Hayes et al. 2009a; Vanraden et al. 2009). One reason for the disagreement between simulated and real data results could be that the genetic architecture simulated is significantly different from what is found in real populations. Most studies published to date that compare methods using simulated architectures have considered only 50 or fewer QTL affecting the trait (e.g., Meuwissen et al. 2001; Habier et al. 2007; Lund et al. 2009). In this article we hypothesize that the relative utility of genome-wide evaluation methods depends significantly on both the genomic structure of the population and the genetic trait architecture.The main objective of this study was to compare a linear method, GBLUP, and a nonlinear variable selection method, BayesB, using simulated data across a range of population and trait genetic architectures to further understand the mechanics of genome-wide evaluation methods. An important secondary objective was to extend deterministic prediction models to predict the accuracy of both methods. Theoretical models complement stochastic simulation by helping the understanding of the factors involved in genome-wide evaluation performance and, in return, stochastic simulation is used to confirm theoretical derivations.     

Population Genetic Structure of Wild Boars in Poland

The analysis involved wild boars from the Lublin region, Warmia and Mazury, and Wielkopolska. The study material comprised muscle tissue samples collected from 100 wild boars. We analysed loci S0008, SW1129, SW986, SW1465, SW1492, SW1514, SW2532, SW461, SW841, SW2021, and SW2496 [1, 2]. The largest number of specific alleles, i.e. in six loci, was observed in wild boars from Warmia and Mazury; in turn, there were only two alleles in the group of wild boars from Lublin, and no alleles in individuals from Wielkopolska. The average value of the observed heterozygosity was H_o = 0.51, and the average value of expected heterozygosity was H_e = 0.63. PIC was another analysed indicator, with its lowest value determined for wild boars from the Wielkopolska region (0.53), and the highest value (0.62) was found for the animals from Warmia and Mazury. In the study population of wild boars, we also determined the F_ST index, which was 0.073, and N_m had a value greater than 3 (3.15); therefore, it can be concluded that the number of migrants per generation was 3. Both coefficients confirm the possibility of gene transfer and reproduction within and between the analysed populations of the wild boars. In our study, we observed a greater genetic distance between the wild boar populations from Wielkopolska and the Lublin and Warmia and Mazury regions in spite of the smaller geographical distance of these lands. This may be caused the less extensive network of ecological corridors as well as the occurrence of anthropogenic barriers e.g. large urban centres, an extensive network of roads, and the high volume of traffic in the direction of the capital.     

Genetic Heterogeneity in Wild Isolates of Cellular Slime Mold Social Groups

This study addresses the issues of spatial distribution, dispersal, and genetic heterogeneity in social groups of the cellular slime molds (CSMs). The CSMs are soil amoebae with an unusual life cycle that consists of alternating solitary and social phases. Because the social phase involves division of labor with what appears to be an extreme form of “altruism”, the CSMs raise interesting evolutionary questions regarding the origin and maintenance of sociality. Knowledge of the genetic structure of social groups in the wild is necessary for answering these questions. We confirm that CSMs are widespread in undisturbed forest soil from South India. They are dispersed over long distances via the dung of a variety of large mammals. Consistent with this mode of dispersal, most social groups in the two species examined for detailed study, Dictyostelium giganteum and Dictyostelium purpureum, are multi-clonal.     

Genetic Variation at the MHC in a Population of Introduced Wild Turkeys

Genetic variation in the major histocompatibility complex (MHC) is known to affect disease resistance in many species. Investigations of MHC diversity in populations of wild species have focused on the antigen presenting class IIβ molecules due to the known polymorphic nature of these genes and the role these molecules play in pathogen recognition. Studies of MHC haplotype variation in the turkey (Meleagris gallopavo) are limited. This study was designed to examine MHC diversity in a group of Eastern wild turkeys (Meleagris gallopavo silvestris) collected during population expansion following reintroduction of the species in southern Wisconsin, USA. Southern blotting with BG and class IIβ probes and single nucleotide polymorphism (SNP) genotyping was used to measure MHC variation. SNP analysis focused on single copy MHC genes flanking the highly polymorphic class IIβ genes. Southern blotting identified 27 class IIβ phenotypes, whereas SNP analysis identified 13 SNP haplotypes occurring in 28 combined genotypes. Results show that genetic diversity estimates based on RFLP (Southern blot) analysis underestimate the level of variation detected by SNP analysis. Sequence analysis of the mitochondrial D-loop identified 7 mitochondrial haplotypes (mitotypes) in the sampled birds. Results show that wild turkeys located in southern Wisconsin have a genetically diverse MHC and originate from several maternal lineages.     

环境因子对大石鸡种群遗传结构的影响

大石鸡是我国特有种 ,仅分布于青海东部 ,甘肃中部 ,宁夏六盘山以西 ,是我国北方干旱和半干旱荒漠环境指示鸟类。研究其遗传多样性与环境变化的关系 ,不仅是生态遗传学的前沿领域 ,而且在进化生物学和保护生物学领域都有重要的理论意义。采用聚合酶链式反应 ( PCR)和直接测序的方法 ,测定了甘肃境内由北向南的 5个大石鸡 ( Alectorismagna)种群 (兰州、榆中、定西、武山和礼县 )的线粒体 DNA( mt DNA)控制区 ( D-loop) 4 5 7～ 4 5 8个碱基长度的基因序列。结果表明兰州、榆中、定西、武山和礼县种群的平均碱基含量中 A( F=0 .30 F0 .0 1( 4 ,32 ) =3.97)、T( F=6 .4 4>F0 .0 1( 4 ,32 ) =3.97)差异极显著。 5个种群的基因变异率分别为 0 .32± 0 .2 7%、0 .4 8± 0 .4 5 %、0 .6 2± 0 .4 3%、0 .4 4± 0 .2 4 %、0 .1 7± 0 .1 4 % ,种群内的平均基因变异率为 0 .4 1± 0 .1 7% ,种群间的平均基因变异率为 0 .4 6± 0 .1 0 % ,种群内和种群间的平均基因变异率差异不明显( F=2 .5 90 .0 5 )和无霜期 ( r=-0 .81 0     

细菌群体的异质性

发生在由一祖先细胞形成的菌悬液、菌落或生物膜中的细菌群体异质性,可以使群体在面临多种胁迫环境时,通过各亚群间的协同作用生存下去。这种分化不仅有表型差异,而且还通过细胞间的遗传物质交换和细胞内的自发突变在群体水平上产生遗传差异。细菌群体的这种异质性分化可能是细菌适应环境的的根本源泉。     

The Impact of Accelerating Faster than Exponential Population Growth on Genetic Variation

Current human sequencing projects observe an abundance of extremely rare genetic variation, suggesting recent acceleration of population growth. To better understand the impact of such accelerating growth on the quantity and nature of genetic variation, we present a new class of models capable of incorporating faster than exponential growth in a coalescent framework. Our work shows that such accelerated growth affects only the population size in the recent past and thus large samples are required to detect the models’ effects on patterns of variation. When we compare models with fixed initial growth rate, models with accelerating growth achieve very large current population sizes and large samples from these populations contain more variation than samples from populations with constant growth. This increase is driven almost entirely by an increase in singleton variation. Moreover, linkage disequilibrium decays faster in populations with accelerating growth. When we instead condition on current population size, models with accelerating growth result in less overall variation and slower linkage disequilibrium decay compared to models with exponential growth. We also find that pairwise linkage disequilibrium of very rare variants contains information about growth rates in the recent past. Finally, we demonstrate that models of accelerating growth may substantially change estimates of present-day effective population sizes and growth times.     

Genetic Heterogeneity in a Natural Population of Acanthamoeba polyphaga from Soil,an Isoenzyme Analysis1

Acanthamoeba polyphaga, a free-living, bacterial feeder found in freshwater and soil, reproduces asexually and is morphologicaly distinguishable from other acanthamoebae. Isoenzyme analyses were done on 15 random, clonal isolates from soil. Electrophoretic patterns indicated that enzyme bands occurred in clusters consistent with that of a diploid organism. The data indicates that natural populations of A. polyphaga have a greater genetic diversity than laboratory isolates of other amoebae, resembling the heterogeneity observed for natural populations of bacteria.     

利用ISSR标记研究野大豆居群内遗传变异及其取样策略

为了有效地保护野大豆(Glycine soja Sieb.et Zucc.)并制定合理的居群取样策略,对上海江湾机场的一个天然野大豆居群进行了100个单株(个体)的随机取样,并用ISSR分子标记对其进行了遗传多样性分析。利用筛选出的15条ISSR引物在这个居群中检测到较高的遗传变异,样本内个体间的相似系数变化在0．17～0．89之间。居群内平均每个位点的平均预期杂合度(He)为0．1714,香农指数(I)为0．2714。PCA分析显示,江湾野大豆居群内的遗传变异不是呈均匀分布,而是呈丛状分布。该野大豆居群遗传多样性和样本内个体数量间的相关性分析显示：在个体数少于40的情况下,遗传多样性随个体数的增加而迅速增加：当样本中的个体数大于40时,遗传多样性的增加减慢并很快趋于饱和。研究表明：对野大豆居群进行异地保护时,对各居群的采样植株数不应当低于35～45;在居群内采样时,所采集的个体之间最好相隔一定的空间距离。     

利用ISSR标记研究野大豆居群内遗传变异及其取样策略

为了有效地保护野大豆(Glycine soja Sieb.et Zucc.)并制定合理的居群取样策略,对上海江湾机场的一个人然野大豆居群进行了 100个单株(个体)的随机取样,并用ISSR分子标记对其进行了遗传多样性分析.利用筛选出的15条ISSR引物在这个居群中检测到较高的遗传变异,样本内个体间的相似系数变化在0.17～0.89之间.居群内平均每个位点的平均预期杂合度(He)为0.171 4,香农指数(I)为0.271 4.PCA分析显示,江湾野大豆居群内的遗传变异不是呈均匀分布,而是呈从状分布.该野大豆居群遗传多样性和样本内个体数量间的相关性分析显示:在个体数少于40的情况下,遗传多样性随个体数的增加而迅速增加;当样本中的个体数大于40时,遗传多样性的增加减慢并很快趋于饱和.研究表明:对野大豆居群进行异地保护时,对各居群的采样植株数不应当低于35～45;在居群内采样时,所采集的个体之间最好相隔一定的空间距离.     

The Effects of a Natural Increase in Food-Supply on a Wild Population of House Mice

Changes in density and breeding of the house mouse (Mus musculus) in a New Zealand forest dominated by hard beech (Nothofagus truncata) were monitored for 2.5 years. Mice bred during winter and increased dramatically in density only during a beech mast year. Mice readily ate the endosperm and embryo of hard beech seed in die laboratory and chemical analysis showed it to be a very nutritious food source, similar in quality to Fagus beech seed in the northern hemisphere. Thus the mouse, introduced to New Zealand, responds to a Nothofagus mast year in a similar way to other rodent species in the northern hemisphere during a Fagus mast year.     

Complex Genetic Architecture of Cardiac Disease in a Wild Type Inbred Strain of Drosophila melanogaster

Natural populations of the fruit fly, Drosophila melanogaster, segregate genetic variation that leads to cardiac disease phenotypes. One nearly isogenic line from a North Carolina peach orchard, WE70, is shown to harbor two genetically distinct heart phenotypes: elevated incidence of arrhythmias, and a dramatically constricted heart diameter in both diastole and systole, with resemblance to restrictive cardiomyopathy in humans. Assuming the source to be rare variants of large effect, we performed Bulked Segregant Analysis using genomic DNA hybridization to Affymetrix chips to detect single feature polymorphisms, but found that the mutant phenotypes are more likely to have a polygenic basis. Further mapping efforts revealed a complex architecture wherein the constricted cardiomyopathy phenotype was observed in individual whole chromosome substitution lines, implying that variants on both major autosomes are sufficient to produce the phenotype. A panel of 170 Recombinant Inbred Lines (RIL) was generated, and a small subset of mutant lines selected, but these each complemented both whole chromosome substitutions, implying a non-additive (epistatic) contribution to the “disease” phenotype. Low coverage whole genome sequencing was also used to attempt to map chromosomal regions contributing to both the cardiomyopathy and arrhythmia, but a polygenic architecture had to be again inferred to be most likely. These results show that an apparently simple rare phenotype can have a complex genetic basis that would be refractory to mapping by deep sequencing in pedigrees. We present this as a cautionary tale regarding assumptions related to attempts to map new disease mutations on the assumption that probands carry a single causal mutation.     

环境因子对雉鸡甘肃亚种种群遗传多样性的影响(英文)

采用聚合酶链式反应(PCR)和直接测序的方法,测定了雉鸡甘肃亚种9个种群118个样本的线粒体DNA(mtDNA)控制区(D-loop)1150个碱基长度的基因序列,43个变异位点产生51个单倍型。环境因子与种群遗传变异的相关性研究表明,序列变异与经度(r=0.725,P<0.05)、年平均温度(r=0.833,P<0.05)呈显著正相关,核苷酸多样性与经度(r=0.686,P<0.05)、年平均温度(r=0.844,P<0.05)呈显著正相关。片段化与低温是导致雉鸡甘肃亚种遗传多样性的主要因素。序列变异及核苷酸多样性与温度的变异系数呈显著负相关(r序列=-0.679,P<0.05;r核苷酸=-0.669,P<0.05)。温度越稳定地区雉鸡甘肃亚种的遗传多样性越高。     

Genetic Architecture of Skin and Eye Color in an African-European Admixed Population

Variation in human skin and eye color is substantial and especially apparent in admixed populations, yet the underlying genetic architecture is poorly understood because most genome-wide studies are based on individuals of European ancestry. We study pigmentary variation in 699 individuals from Cape Verde, where extensive West African/European admixture has given rise to a broad range in trait values and genomic ancestry proportions. We develop and apply a new approach for measuring eye color, and identify two major loci (HERC2[OCA2] P = 2.3×10⁻⁶², SLC24A5 P = 9.6×10⁻⁹) that account for both blue versus brown eye color and varying intensities of brown eye color. We identify four major loci (SLC24A5 P = 5.4×10⁻²⁷, TYR P = 1.1×10⁻⁹, APBA2[OCA2] P = 1.5×10⁻⁸, SLC45A2 P = 6×10⁻⁹) for skin color that together account for 35% of the total variance, but the genetic component with the largest effect (∼44%) is average genomic ancestry. Our results suggest that adjacent cis-acting regulatory loci for OCA2 explain the relationship between skin and eye color, and point to an underlying genetic architecture in which several genes of moderate effect act together with many genes of small effect to explain ∼70% of the estimated heritability.     

The Impact of Phenotypic and Genetic Heterogeneity on Results of Genome Wide Association Studies of Complex Diseases

Phenotypic misclassification (between cases) has been shown to reduce the power to detect association in genetic studies. However, it is conceivable that complex traits are heterogeneous with respect to individual genetic susceptibility and disease pathophysiology, and that the effect of heterogeneity has a larger magnitude than the effect of phenotyping errors. Although an intuitively clear concept, the effect of heterogeneity on genetic studies of common diseases has received little attention. Here we investigate the impact of phenotypic and genetic heterogeneity on the statistical power of genome wide association studies (GWAS). We first performed a study of simulated genotypic and phenotypic data. Next, we analyzed the Wellcome Trust Case-Control Consortium (WTCCC) data for diabetes mellitus (DM) type 1 (T1D) and type 2 (T2D), using varying proportions of each type of diabetes in order to examine the impact of heterogeneity on the strength and statistical significance of association previously found in the WTCCC data. In both simulated and real data, heterogeneity (presence of “non-cases”) reduced the statistical power to detect genetic association and greatly decreased the estimates of risk attributed to genetic variation. This finding was also supported by the analysis of loci validated in subsequent large-scale meta-analyses. For example, heterogeneity of 50% increases the required sample size by approximately three times. These results suggest that accurate phenotype delineation may be more important for detecting true genetic associations than increase in sample size.     

A Multivariate Analysis of Genetic Constraints to Life History Evolution in a Wild Population of Red Deer

Evolutionary theory predicts that genetic constraints should be widespread, but empirical support for their existence is surprisingly rare. Commonly applied univariate and bivariate approaches to detecting genetic constraints can underestimate their prevalence, with important aspects potentially tractable only within a multivariate framework. However, multivariate genetic analyses of data from natural populations are challenging because of modest sample sizes, incomplete pedigrees, and missing data. Here we present results from a study of a comprehensive set of life history traits (juvenile survival, age at first breeding, annual fecundity, and longevity) for both males and females in a wild, pedigreed, population of red deer (Cervus elaphus). We use factor analytic modeling of the genetic variance–covariance matrix (G) to reduce the dimensionality of the problem and take a multivariate approach to estimating genetic constraints. We consider a range of metrics designed to assess the effect of G on the deflection of a predicted response to selection away from the direction of fastest adaptation and on the evolvability of the traits. We found limited support for genetic constraint through genetic covariances between traits, both within sex and between sexes. We discuss these results with respect to other recent findings and to the problems of estimating these parameters for natural populations.     

野生与人工驯养长爪沙鼠群体遗传结构比较分析

目的探索野生与人工驯养的长爪沙鼠群体遗传状况。方法采用12个微卫星引物,对银川与呼和浩特地区捕获的野生长爪沙鼠群体和首都医科大学人工驯养20余年的长爪沙鼠群体的遗传结构进行比较分析。结果12个微卫星位点中有等位基因29个,3个群体的平均等位基因数分别为2.4167、2.2500、2.2500,平均有效等位基因数分别为1.7505、1.7195、1.6968;有11个微卫星位点呈现多态,多态位点百分率分别为91.67%、83.33%、83.33%,香隆指数分别为0.6239、0.5962、0.5591;平均观测杂合度分别为0.5231、0.5051、0.4825,平均期望杂合度分别为0.4008、0.3882、0.3655;银川和首医群体之间的遗传距离最大,为0.1033;呼和浩特和首医群体之间的距离最小,为0.0592。结论3个群体处于Hardy-Weinberg平衡状态,3个群体之间及与总体之间的遗传结构差异无显著性（P〉0.05）。     

基于SSR标记的新疆野杏群体遗传多样性及遗传结构

利用27对SSR分子标记对新疆4个野杏群体遗传多样性和遗传结构进行分析,评价新疆野杏遗传多样性水平和分化程度,为新疆野杏合理保护与利用提供科学依据。结果显示：（1）27对SSR引物共检测到431个等位基因（N_a）,各位点平均等位基因数（N_a）和多态性信息含量（PIC）分别为15.96和0.84;物种水平上Shannons信息指数（I）和期望杂合度（H_e）分别为2.21和0.78。（2）群体水平上等位基因数（N_a）、有效等位基因（N_e）、Shannons信息指数（I）、期望杂合度（H_e）和观察杂合度（H_o）分别为10.98、5.85、1.92、0.79和0.55;其中新源县野杏群体遗传多样性最丰富,巩留县群体遗传多样性最低。（3）基于F统计量分析的遗传分化系数（F_st）为0.05,基因流（N_m）为5.26;分子方差分析显示新疆野杏群体大部分遗传变异来自群体内（95.4%）,群体间的遗传变异仅占4.6%。（4）新疆野杏群体遗传距离为0.06~0.49,平均为0.24;遗传相似度为0.61~0.94,平均为0.80;遗传相似度的聚类分析和遗传距离的主坐标分析结果一致,均将供试4个群体划分为两组;Mantel检测显示,新疆野杏群体遗传距离与地理距离无显著相关（r=0.332,P＝0.16）。研究表明,新疆野杏资源具有丰富的遗传多样性,群体遗传分化程度较低,群体间遗传距离较小,这与新疆野杏群体的大小和悠久的演化历史以及群体间频繁的基因交流相关。