河南汉族群体6个STR基因座遗传多态性研究

对河南省河南籍汉族群体的6个短串联重复序列（Short tandem repeats,STR)基因座等位基因频率进行研究,得到河南汉族群体F13A1,F13B,D8S1179,CSF1PO,D5S818,TPOX基因座的群体遗传学依据。EDTA抗凝血样采自河南122名无血缘关系的汉族个体,采用Chelex法抽提DNA,PCR扩增,非变性聚丙烯酰胺垂直凝胶电泳,银染显色分析,得到6个基因座的等位基因频率,各基因座的杂合度分别为：0.62,0.46,0.83,0.59,0.78,0.65;人体识别率分别为0.78,0.66,0.95,0.79,0.92,0.82。6个STR基因座具有较高的杂合度,等位基因分布符合Hardy-Weinberg平衡,是较理想的遗传标记,可用于法医学个本识别和亲权鉴定。     

中国普米族、傈僳族STR遗传多态性研究

采用荧光标记STR基因扫描技术对普米族和傈僳族进行了STR多态性调查,9个STR基因座在普米族群体中,检出85个等位基因,194种基因型,其频率分布在0．0050－0．5250和0．0098－0．3235,在傈僳族群体中,共检出63个等位基因,145种基因型,其频率分布在0．0050－0．4802和0．0099－0．3664,χ2检验表明,各基因座的基因型分布符合Hardy-Weinberg平衡定律（P＞0．05）,统计学结果显示,这些遗传标记在普米族和傈僳族群体中,杂合度均大于0．6,平均多态信息量高于0．7,个体识别力在0．8以上,非父排除率也都超过了0．5,说明实验所选STR标记对民族群体遗传学研究是极为有价值的。     

新疆4个民族STR基因座遗传多态性研究

对新疆维吾尔放族,锡伯族,乌孜别克族,柯尔克孜族4个民族的400份样本和40个家系进行STR基因扫描,基因分型和遗传结构分析。获得了4个民族STR遗传特征及遗传方式等的科学数据。结果为9个STR基因座上维吾尔族有66种STR等位基因,148种基因型;锡伯族有72种STR等位基因,163种基因型;乌孜别克族有65种TSR等位基因,168种基因型;柯尔克孜族有71种STR等位基因,191种基因型,用新疆4个民族的数据和汉族人群,美国高加索人群,美国黑人相比较发现,中国民族遗传特征数据之间差异不显著,而和国外民族相比差异显著,进一步证明中华民族是一个不可分割的大家庭。     

新疆维吾尔族四个STR位点遗传多态性分析

研究新疆维吾尔族人群D16S539、D13S317、D7S820和D5S818的STR基因位点的基因及基因型分布,获得4个基因座的群体遗传学数据。采用PCR扩增技术和基因扫描技术进行样本STR遗传结构分析,并与其他种族、人群的等位基因频率进行比较。结果表明4个基因位点在新疆维吾尔族人群中均具有遗传多态性。4个基因座的基因型分布均符合Hardy-Weinberg平衡定律（P＞0.05）,不同人群基因频率分布存在一定的差异,所得到的等位基因频率等数据可为遗传学研究、法医个体畜产品识别及亲子鉴定提供依据。     

三个STR位点在哈萨克族中的遗传多态性

运用复合PCR扩增,6％变性聚丙烯酰胺凝胶电泳结合银染技术对我国新疆102位无关的哈萨克族个体进行D16S539,D7S820,D13S317的STR位点的调查,为建立新疆哈萨克族群体数据库提供资料。经统计学检验,3个位点的基因型频率分布符合Hardy-Weinberg平衡定律,结果显示3个位点的期望杂合度为：0.9439、0.9356、0.9304,累积PIC＝0.9905,DP＝0.9998,PE=9572。紫外,比较新疆哈萨克族与其他4个人群的等位片段频率,发现除与北京汉族在D7S820位点上无统计学意义外（P＞0.05）,其他均可见显著性差异（P＜0.05）。同时,在8个家系42人的调查中无一突变发现且均按孟德尔遗传规律传递。3个STR位点的联合分析在法医学应用及群体遗传学中显示了较高的价值。     

人类基因组STR等位基因阶梯的研制

研究建立一种制备STR等位基因阶梯标准的新方法。以单一来源的DNA链为模板,采用槽式PCR扩增法,并经过PAGE胶回收纯化制备等位基因阶梯标准。结果：该方法适合等位基因阶梯标准的制备,所制备的等位基因阶梯基本无杂带,效果较理想。     

中国广西壮族9个STR基因座遗传多态性研究

选择9个STR基因座（D3S1358、vWA、FGA、TH01、TPOX、CSF1PO、D5S818、D13S317、D7S820）,采用四色荧光标记STR基因扫描技术,对中国广西壮族的群体遗传多态性进行研究,检测91名无关个体血液样本,共检出62种等位片段,其频率分布在0．0054－0．5495之间;检出169种基因型,其频率分布在0．0110－0．3297之间。9个STR基因座的基因型频率期望与观察值均符合Hardy-Weinberg平衡定律（P＞0．05）。9个基因座多态信息量（polymorphic information content)PIC≥0．6088,杂合度（heterozygosity)H≥0．8165。计算种族,民族之间的遗传距离并对之进行比较,结果显示,中国广西壮族与美国白人及美国黑人存在显著差异,与黑人之间的差异大于与白人之间的差异;广西壮族与西安汉族的关系近于与其他少数民族的关系,种族民族之间的聚类分析结果显示,现有资料分为黑种人,白种人和黄种人（我国各民族）3类。     

奶牛和肉牛6个STR基因座遗传多态性研究

利用PCR技术和复合电泳银染技术检测奶牛和肉牛BM2113、BM1862、BMc701、BM2934、TGLA122、BM720等6个STR基因座的多态性分布,并计算该6个基因座的基因频率(P_i)、个体鉴别力(DP)、杂合度(H)、多态信息含量(PIC)、和非父排除概率(PE)。结果显示:6个STR基因座的基因型分布符合Hardy-Weinberg平衡,奶牛中6个STR基因座中BM2113基因座的DP、H和PIC最高,TGLA122基因座的PE最高。6个STR基因座的累积个体鉴别力(CDP)为0.99997,累积非父排除能力(CPE)为0.98827。肉牛中6个STR基因座中BM1862基因座的DP、H、PIC、PE都是最高,6个STR基因座的累积个体鉴别力(CDP)为0.99999,累积非父排除能力(CPE)为0.99578。结果表明,6个STR基因座可用于牛的遗传连锁分析、个体识别和亲子鉴定等研究领域。     

云南怒族STR基因座遗传多态性研究

本文选择9个STR基因座和Amelogenin基因座,利用基因测序,采用基因扫描技术,对云南怒族聚集地区84名无关个体血样进行研究,建立了云南怒族9个STR基因座的基因频率数据库。用χ2检验,9个STR基因座基因型分布符合Hardy-Weinberg平衡定律。与其他民族资料一样,本课题所获得的云南怒族9个STR基因座数据是一组有价值的DNA多态性遗传标记资料。为建立我国不同民族STR基因数据库提供了资料。 Abstract:In this study,blood samples were randomly drawn from 84 unrelated Nu individuals.The polymorphism of nine STR loci and Amelogenin locus were determined by DNA GeneScan.The genetic database on the distribution of gene frequency on the nine STR loci was established,statistical results showed that the genotype distributions were in agreement with Hardy-Weinberg equation.Compared with other population,the results in our study were of great value in human DNA genetic data instant method with the characteristics of precision and sensitivity.     

中国阿昌族九个STR基因位点遗传多态性研究

采集云南阿昌族100个无关个体血样,研究该民族9个STR位点和Amelogenin基因位点,采用四色荧光标记STR基因扫描技术,同时检测96个样品,建立云南阿昌族9个STR位点的基因频率数据库,共检测出69种等位基因,其频率分布在0．0050－0．6100,166种基因型,其基因型频率分布在0．0100－0．3900,平均H为0．7381,累积DP为0．9999999,EPP为0．9999989,9个STR位点基因型分布符合Handy-Weiberg平衡定律,为建立我国不同民族STR基因数据奠定了基础,将在人类学,法医学和民族学领域发挥重要的应用价值。     

种群微卫星DNA分析中样本量对各种遗传多样性度量指标的影响

我们以中国飞蝗种群的微卫星遗传分析数据为例 ,评估了取样对种群遗传多样性指标的影响 ,结果显示 :样本大小与所观测到的每位点等位基因数、平均等位基因数及基因丰富度指数均呈显著正相关 ,而与期望杂合度无显著相关 ;微卫星位点多态性的高低直接影响所观测到的种群基因丰富度及其检测所需的样本量 ;对大多数种群遗传和分子生态学研究而言 ,30 - 5 0个个体是微卫星DNA分析所需要的最小样本量。基因丰富度经过稀疏法或多次随机抽样法校正后 ,可适用于瓶颈效应等种群历史数量变动的检测。另外 ,在研究中 ,还应避免采集时间的不同及样本的性比构成所可能造成的对种群遗传结构的影响     

群体遗传学研究中STR数据的统计方法应用

STR作为遗传多态性较高的标记, 被广泛地运用于群体遗传学的研究。对于STR分型产生的基因型频率及等位基因频率数据, 文章总结了各种参数指标的计算及分析方法。其中参数指标包括杂合度、多态信息量、连锁不平衡系数、近交系数、遗传距离以及固定指数等; 分析方法包括主成分分析、系统发生树、分子方差分析、R矩阵、地理信息系统以及空间自相关分析。通过这些参数指标及分析方法的使用, 可以既直观又科学地揭示群体遗传结构、群体间遗传分化以及人类起源与进化等群体遗传学中研究的关键问题。     

广西环江县毛南族九个短串联重复序列基因座的遗传学分析

为了了解广西环江毛南族人群无关个体的九个短串联重复序列:vWA,D18S51,D5S818,FGA,D8S1179,D21S11,D7S820,D3S1358,D13S317基因座的遗传多态性分布情况;本文用枸橼酸钠抗凝法采集广西环江县毛南族200份无亲缘关系的健康个体的血样,Chelex-100方法提取DNA,应用AmpFlSTRIdentifilerTM荧光标记复合扩增技术对血样DNA的九个STR基因座进行扩增,用ABI 3100型遗传分析仪对扩增产物进行检测。结果显示九个STR位点的基因型分布均符合Hardy-Weinberg平衡定律,累积非父排除率达0.999996,累积个体识别能力达0.99999999996,多态信息总量为0.9999985。结论:广西环江县毛南族人群有自身的STR等位基因分布特征,所获数据可为法医学个体识别、亲子鉴定及群体的遗传学研究提供依据。     

Cryptic population genetic structure: the number of inferred clusters depends on sample size

Clustering methods have been used extensively to unravel cryptic population genetic structure. We investigated the effect of the number of individuals sampled in each location on the resulting number of clusters. Our study was motivated by recent results in Arabidopsis thaliana: studies in which more than one individual was sampled per location apparently have led to a much higher number of clusters than studies where only one individual was sampled in each location, as is generally done in this species. We show, using computer simulations and microsatellite data in A. thaliana, that the number of sampled individuals indeed has a strong impact on the number of resulting clusters. This effect is smaller if the sampled populations have a hierarchical structure. In most cases, sampling 5–10 individuals per population should be enough. The results argue for abandoning the concept of ‘accessions’ in partially selfing organisms.     

Effects of sample size,number of markers,and allelic richness on the detection of spatial genetic pattern

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially‐explicit, individual‐based program to simulate gene flow in a spatially continuous population inhabiting a landscape with gradual spatial changes in resistance to movement. We simulated a wide range of combinations of number of loci, number of alleles per locus and number of individuals sampled from the population. We assessed how these three aspects of study design influenced the statistical power to successfully identify the generating process among competing hypotheses of isolation‐by‐distance, isolation‐by‐barrier, and isolation‐by‐landscape resistance using a causal modelling approach with partial Mantel tests. We modelled the statistical power to identify the generating process as a response surface for equilibrium and non‐equilibrium conditions after introduction of isolation‐by‐landscape resistance. All three variables (loci, alleles and sampled individuals) affect the power of causal modelling, but to different degrees. Stronger partial Mantel r correlations between landscape distances and genetic distances were found when more loci were used and when loci were more variable, which makes comparisons of effect size between studies difficult. Number of individuals did not affect the accuracy through mean equilibrium partial Mantel r, but larger samples decreased the uncertainty (increasing the precision) of equilibrium partial Mantel r estimates. We conclude that amplifying more (and more variable) loci is likely to increase the power of landscape genetic inferences more than increasing number of individuals.     

9号染色体短臂上7个STR基因座在基因扫描中的信息表现

为了初步探讨7个位于染色体9p区域的短串联重复序列(shorttandemrepeat,STR)基因座:D9S288、D9S157、D9S1748、D9S171、D9S161、D9S1817和D9S1805在遗传学研究及法医学应用中的意义,随机抽取225名湖南汉族无关个体,复合PCR技术扩增上述基因座,ABI377全自动测序仪进行基因分型,共检出75种等位基因,通过对基因型及等位片断频率分布的研究和数据统计分析,7个基因座基因频率分布在0.002～0.800之间,构成243种基因型。7个STR基因座基因型分布均符合Hardy Weinberg平衡定律(P>0.05),杂合度(heterozygosity,H)介于0 347～0.844之间,个体识别力(discriminationpower,DP)为0.346～0.841,非父排除率(probabilitiesofpaternityexclusion,PPE)为0.308～0.738,多态信息含量(polymorphicinformationcontent,PIC)在0.328～0.822之间。种族比较结果显示,湖南汉族与非洲黑人及欧洲白人在大多数基因座均存在显著差异(P<0.001)。研究结果丰富了中华民族基因数据库,在人类群体遗传学及法医学研究领域有重要应用价值。     

Optimal number of features as a function of sample size for various classification rules

MOTIVATION: Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. RESULTS: Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. AVAILABILITY: For the companion website, please visit http://public.tgen.org/tamu/ofs/ CONTACT: e-dougherty@ee.tamu.edu.     

Genetic data on 15 STR loci in the Caucasian population of the Russian Federation

Population genetic data for the 15 STR loci included in the AmpFlSTR Identifier kit (D8S1179, D21S11, D7S820, CSF1PO, D3S1358, TH01, D13S317, D16S539, D2S1338, D19S433, VWA, TPOX, D18S51, D5S818 and FGA) obtained from 1118 unrelated Caucasian individuals from the Russian Federation are presented. In addition, a number of forensically useful genetic parameters are reported.     

Forensic and population genetic analyses of the GlobalFiler STR loci in the Mongolian population

We have analyzed 24 loci including autosomal and Y-chromosomal short tandem repeats (STRs), Y-indel, and sex-determining marker in a sample of 267 unrelated individuals from the Mongolian population using the GlobalFiler? PCR Amplification Kit to provide an expanded and more reliable forensic database. Khalkh among 15 Mongolian minor-groups accounts for about 80% of the entire Mongolian population. A total of 267 different DNA profiles were found in this work. The highest gene diversity was observed in the SE33 (0.9376) locus, and the lowest value was found in the TPOX (0.6142) locus. Although individual power of discrimination estimates varied at the studied loci, combined probability of match from the 21 STR loci was estimated to be 1.139?×?10^?24, which is highly informative. Based on the results of pairwise F _ST genetic distances and multi-dimensional scaling plot showed that Mongolians were clustered into Europeans and Asians, although Mongolia is geographically located in Northeastern Asia. Thus, the present survey of the Mongolian population may help establish a comprehensive reference database for forensic and population genetic analyses.     

Patterns of genetic diversity at the nine forensically approved STR loci in the Indian populations

Genetic diversity at the nine short tandem repeat (STR) loci, which are universally approved and widely used for forensic investigations, has been studied among nine Indian populations with diverse ethnic, linguistic, and geographic backgrounds. The nine STR loci were profiled on 902 individuals using fluorescent detection methods on an ABI377 System, with the aid of an Amp-F1 Profiler Plus Kit. The studied populations include two upper castes, Brahmin and Kayastha; a tribe, Garo, from West Bengal; a Hindu caste, Meitei, with historical links to Bengal Brahmins; a migrant group of Muslims; three tribal groups, Naga, Kuki and Hmar, from Manipur in northeast India; and a middle-ranking caste, Golla, who are seminomadic herders from Andhra Pradesh. Gene diversity analysis suggests that the average heterozygosity is uniformly high (>0.8) in the studied populations, with the coefficient of gene differentiation at 0.050 +/- 0.0054. Both neighbor-joining (NJ) and unweighted pair group method with arithmetic mean (UPGMA) trees based on DA distances bring out distinct clusters that are consistent with ethnic, linguistic, and/or geographic backgrounds of the populations. The fit of the Harpending and Ward model of regression of average heterozygosity on the gene frequency centroid is found to be good, and the observed outliers are consistent with the population structure and history of the studied populations. Our study suggests that the nine STR loci, used so far mostly for forensic investigations, can be used fruitfully for microevolutionary studies as well, and for reconstructing the phylogenetic history of human populations, at least at the local level.