30个祖先信息位点的筛选及应用

摘要：目的 筛选一组祖先信息SNPs位点（AIMs,Ancestry Informative Markers）,构建复合检测体系,用于东亚、欧洲和非洲人群遗传成分描述及个体种族来源推断。方法 以HapMap数据库9个人群的658份样本的分型数据为基础,从30个表型相关基因总共282个SNPs位点中筛选出30个AIMs位点,基于微测序-通用芯片技术构建复合检测体系,并建立人群等位基因频率数据库。使用这组位点分析HapMap数据库中658份人群样本,初步验证位点的区分效能;然后,使用研究构建的体系检验收集的5个人群194份无关个体的DNA样本。最后,通过Structure软件分析获取人群的成分构成以及个体的遗传成分,对个体样本进行种族来源推断。 结果 筛选的30个AIMs位点符合哈迪温伯格平衡（p>0.01）,位点之间没有连锁（r2<0.1）, 658份HapMap数据库样本和194份实验样本的祖先成分分析结果与已知结果完全一致。 结论 本文筛选并建立的30个AIMs位点复合检测体系,能够有效实现东亚、欧洲、非洲人群及混合人群的成分构成和个体遗传成分的分析,有效控制遗传连锁分析中由于人群分层现象带来的误差,也可以用于法医DNA检验中个体祖先来源推断。     

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。     

东亚三族群SNP高分辨推断模型构建与效能评估

单核苷酸多态性(single nucleotide polymorphism,SNP)是法医遗传学个体识别和族群推断常用的遗传标记.本研究集合文献和公共库中祖先信息SNP位点(ancestry informative SNPs,AISNPs),应用softmax回归、支持向量机和随机森林3种算法,研究东亚北方的3个主体...     

北京市华北落叶松优树群体遗传多样性分析

利用SSR分子标记对北京市华北落叶松人工林5个群体的220棵优树进行遗传多样性和群体结构分析。20对SSR引物共检测到81个等位基因,每个位点等位基因数2~8个不等,平均4.05个。群体观测和期望杂合度平均值分别为0.429和0.440,Shannon信息指数和多态性信息含量分别为0.756和0.380。5个群体中,百花山和云蒙山遗传多样性水平最高,雾灵山遗传多样性水平最低。AMOVA分析结果显示,2.65%的遗传变异来自于群体间,剩余97.35%的遗传变异来自于群体内。遗传分化系数仅为0.023,表明北京市华北落叶松优树群体遗传分化程度很低。基于Nei's遗传距离可以将5个群体划分为3个类群,四海镇和雾灵山归为第Ⅰ类,松山归为第Ⅱ类,百花山和云蒙山归为第Ⅲ类。STRUCTURE群体结构分析结果与上述聚类分析结果大体一致。以上研究为华北落叶松人工林遗传多样性评价和优良种质资源收集、保护和利用提供理论依据。     

基于RAD高通量测序的蓝花楹群体遗传分析

为了解蓝花楹(Jacaranda mimosifolia)种质资源的遗传多样性和群体遗传结构,对168份种质材料进行RAD-seq测序,构建了系统进化树并进行主成分、群体结构和遗传多样性分析。结果表明,比对参考基因组平均比对率为81.02%,平均测序深度23.18×,最终获得45 552个高质量的SNPs。群体遗传结构分析表明,供试蓝花楹可划分为2个大的类群,来自川、渝地区的种质材料基本归为一类;其余地区归为另一类。19个地区的蓝花楹在SNP水平上的遗传多样性较高,云南昆明(YNKM)居群的核苷酸多样性(π)和期望杂合度(He)最大,表现出最高的遗传多样性。因此,来自川、渝地区的蓝花楹具有相对较近的亲缘关系,推断来自同一祖先,而其余地区的种质可能是随机引种栽培。     

49AISNP：东亚北方三个族群遗传来源推断

样本的族群来源推断在法医调查中可发挥重要作用,一个理想的推断体系是用一组较少的遗传标记实现较高的族群推断准确性。本研究调研搜集了区分东亚北方三个族群北方汉族、日本人和韩国人的428个祖先信息SNP (ancestry informative SNP, AISNP),获取了其在三个族群307份样本中的分型,通过位点Fst值及等位基因频率聚类等信息进一步精简位点,最终得到了一组49AISNP组合。基于307份样本利用留一法对49AISNP进行推断准确性验证,结果表明其在北方汉族、日本和韩国族群中的推断准确性均高于99%。49AISNP组合将有助于东亚地区亚族群的进一步区分。     

基于简化基因组技术的云南蓝果树群体遗传分析

极小种群野生植物云南蓝果树是国家和云南省实施极小种群野生植物保护工程的代表性物种。为有效保护其遗传资源,本研究通过二代测序技术,对其进行简化基因组测序,开发一批特异性高的单核苷酸多态性标记,分析现存群体的遗传结构和遗传多样性。经过遗传变异检测,本次研究中共获得SNP位点98 498个,通过样品最低测序深度>2,样品缺失率<0.5,次要基因型频率（MAF）>0.05筛选以后,得到有效SNP位点6 309个。基于过滤后的SNP,运用生物信息学分析方法,对云南蓝果树完成了群体的遗传分析,其中：系统进化树分析将云南蓝果树划分为3大类,研究分析了云南蓝果树各分类的私人等位基因数目（Private）、平均观测杂合度（H_o）、平均期望杂合度（H_e）、核苷酸多样性（π）和平均近交系数（F_IS）5个遗传多样性参数;群体结构和主成分分析进一步证明了,云南蓝果树现存植株之间亲缘关系较远,遗传多样性差异较大,具有很高的遗传资源保存价值。本研究结果将为基于遗传管理的云南蓝果树就地保护、遗传资源保存和种群重建等保护工程提供科学依据。     

我国6个地方绵羊品种微卫星DNA多态性研究

利用聚丙烯酰胺凝胶电泳技术研究了我国蒙古羊、乌珠穆沁羊、哈萨克羊、阿勒泰羊、滩羊和藏绵羊 6个地方绵羊品种 17个微卫星标记的多态性 ,以探讨其遗传多样性、起源分化及群体间的遗传亲缘关系。结果表明微卫星标记不同位点间遗传多样性差异极显著 (P <0 0 1) ,群体间多态信息含量 (PIC)、近交程度 (Fis)和观察杂合度 (Obs .Het)差异不显著 ,但基因多样性 (genediversity)和期望杂合度 (Exp .Het)差异显著 (P <0 0 5 )。所研究的我国 6个地方绵羊品种与欧洲品种具有相似的遗传多样性 ,但具有较高的近交系数。个体和群体的聚类分析结果提示我国地方绵羊品种可能起源于两类祖先。群体间的聚类分析结果还表明 ,蒙古羊与乌珠穆沁羊分化不明显且具有较近的遗传亲缘关系 ,蒙古羊与藏绵羊间分化明显且具有较远的遗传亲缘关系。滩羊、阿勒泰羊以及藏绵羊间也具有较近的遗传亲缘关系。所研究的我国 6个地方绵羊品种的遗传分化 (Fst)与西班牙绵羊品种接近 ,但明显小于欧洲其他绵羊品种     

光温敏二系杂交小麦恢复系遗传多样性和群体结构分析

为揭示光温敏雄性不育小麦恢复系资源的遗传基础,选用49个Genomic-SSR和40个EST-SSR标记位点对100份冬性光温敏雄性不育小麦恢复系进行遗传多样性和群体结构分析.结果表明：89个位点共扩增出531个等位变异,平均每个位点5.96个; 平均基因多样性和多态性信息量（PIC）分别为0.63和0.57,说明本研究所选用的恢复系的遗传多样性比较丰富;利用NJ法聚类和Structure群体结构分析均将100份恢复系划分为6大类群,且聚类结果基本吻合,同时揭示出北方冬麦区和黄淮海冬麦区恢复系间存在较广泛的基因交流;群体结构分析阐明了各恢复系的遗传组成,推测58%的恢复系血缘相对比较单一,42%的恢复系拥有混合来源.研究结果为新恢复系的选育和现有恢复系的利用提供了理论依据,并为重要农艺性状数量性状位点的关联分析奠定了基础.     

新疆罗布羊群体遗传多样性及系统进化分析

[目的]新疆罗布羊群体遗传变异与起源分化的研究,可为罗布羊品种形成、保护和种质特性研究利用提供理论基础。[方法]利用7个微卫星(SSR)位点及mt DNA D-loop环序列分析了新疆尉犁地区120头罗布羊群体遗传多样性,及与其它新疆南部地方羊种与中国绵羊的三大母系:藏羊、蒙古羊和哈萨克羊,三个野羊种:羱羊、摩佛伦羊、盘羊和亚洲型A型、欧洲型B型的母系遗传距离与进化关系。[结果]罗布羊群体平均等位基因数(K)、观察杂合度(HO)、期望杂合度(HE)、多态信息含量(PIC)分别为8.86、0.711、0.791和0.769;发现BM143位点存在罗布羊群体HW不平衡现象。罗布羊分成A系、B系和C系3个进化系,B系进化支与欧洲B型和多浪羊遗传距离较近,聚为一类;C系进化支先与巴音布鲁克羊聚为一支,然后和A进化支聚成一类,再与新疆其它地方羊种及蒙古羊、藏羊、亚洲型A型聚为一类。三个支系中B支系与摩佛伦羊(O.musmon)的关系较近。[结论]新疆尉犁地区罗布羊群体遗传多样性丰富,具有较高育种价值;群体微卫星BM143位点存在的HW不平衡现象;罗布羊有3个进化系,聚类分析结果初步认为罗布羊是由中东经蒙古高原到达新疆,后来与新疆南部地方羊种混杂的品种。     

A Panel of Ancestry Informative Markers for the Complex Five-Way Admixed South African Coloured Population

Admixture is a well known confounder in genetic association studies. If genome-wide data is not available, as would be the case for candidate gene studies, ancestry informative markers (AIMs) are required in order to adjust for admixture. The predominant population group in the Western Cape, South Africa, is the admixed group known as the South African Coloured (SAC). A small set of AIMs that is optimized to distinguish between the five source populations of this population (African San, African non-San, European, South Asian, and East Asian) will enable researchers to cost-effectively reduce false-positive findings resulting from ignoring admixture in genetic association studies of the population. Using genome-wide data to find SNPs with large allele frequency differences between the source populations of the SAC, as quantified by Rosenberg et. al''s -statistic, we developed a panel of AIMs by experimenting with various selection strategies. Subsets of different sizes were evaluated by measuring the correlation between ancestry proportions estimated by each AIM subset with ancestry proportions estimated using genome-wide data. We show that a panel of 96 AIMs can be used to assess ancestry proportions and to adjust for the confounding effect of the complex five-way admixture that occurred in the South African Coloured population.     

Number of SNPS loci needed to detect population structure

The study of the association of polymorphic genetic markers with common diseases is one of the most powerful tools in modern genetics. Interest in single nucleotide polymorphisms (SNPs) has steadily grown over the last decade. SNPs are currently the most developed markers in the human genome because they have a number of advantages over other marker types. One of the critical problems responsible for 'spurious' association findings in case-control studies is population stratification. There are many statistical approaches developed for detecting population heterogeneity. However the power to detect population structure by known methods is highly dependent on the number of loci utilised. We performed an analysis of SNPs data available in the public domain from The Single Nucleotide Consortia Ltd. (TSCL). Three populations, Afro-American, Asian and Caucasian, were compared. Estimation of the minimum number of SNPs loci necessary for detection of the population structure was performed. Two clustering approaches, distance-based and model-based, were compared. The model-based approach was superior when compared with the distance-based method. We found more than 65 random SNPs loci are required for identifying distinct geographically separated populations. Increasing the number of markers to over 100 raises the probability of correct assignment of a particular individual to an origin group to over 90%, even with conventional clustering methods.     

Mexican American ancestry-informative markers: examination of population structure and marker characteristics in European Americans, Mexican Americans, Amerindians and Asians

Markers with large differences in allele frequencies between ethnicities provide ancestry information that can be applied to genetic studies. We identified over 100 biallelic ancestry informative markers (AIMs) with large allele frequency differences between European Americans (EA) and Pima Amerindians from laboratory and database screens. For 35 of these markers, Mayan, Yavapai and Quechuan Amerindians were genotyped and compared with EA and Pima allele frequencies. Markers with large allele frequency differences between EA and one Amerindian tribe showed only small differences between the Amerindian tribes. Examination of structure in individuals demonstrated a clear separation of subjects of European from those of Amerindian ancestry, and similarity between individuals from disparate Amerindian populations. The AIMs demonstrated the variation in ancestral composition of individual Mexican Americans, providing evidence of applicability in admixture mapping and in controlling for structure in association tests. In addition, a high percentage of single-nucleotide polymorphisms (SNPs) selected on the basis of large frequency differences between EA and Asian populations had large allele frequency differences between EA and Amerindians, suggesting an efficient method for greatly expanding AIMs for use in admixture mapping/structure analysis in Mexican Americans. Together, these data provide additional support for the practical application of admixture mapping in the Mexican American population.Electronic Supplementary Material Supplementary material is available in the online version of this article at     

Development of two multiplex mini-sequencing panels of ancestry informative SNPs for studies in Latin Americans: an application to populations of the State of Minas Gerais (Brazil)

Admixture occurs when individuals from parental populations that have been isolated for hundreds of generations form a new hybrid population. Currently, interest in measuring biogeographic ancestry has spread from anthropology to forensic sciences, direct-to-consumers personal genomics, and civil rights issues of minorities, and it is critical for genetic epidemiology studies of admixed populations. Markers with highly differentiated frequencies among human populations are informative of ancestry and are called ancestry informative markers (AIMs). For tri-hybrid Latin American populations, ancestry information is required for Africans, Europeans and Native Americans. We developed two multiplex panels of AIMs (for 14 SNPs) to be genotyped by two mini-sequencing reactions, suitable for investigators of medium-small laboratories to estimate admixture of Latin American populations. We tested the performance of these AIMs by comparing results obtained with our 14 AIMs with those obtained using 108 AIMs genotyped in the same individuals, for which DNA samples is available for other investigators. We emphasize that this type of comparison should be made when new admixture/population structure panels are developed. At the population level, our 14 AIMs were useful to estimate European admixture, though they overestimated African admixture and underestimated Native American admixture. Combined with more AIMs, our panel could be used to infer individual admixture. We used our panel to infer the pattern of admixture in two urban populations (Montes Claros and Manhua?u) of the State of Minas Gerais (southeastern Brazil), obtaining a snapshot of their genetic structure in the context of their demographic history.     

Integrative analysis of single nucleotide polymorphisms and gene expression efficiently distinguishes samples from closely related ethnic populations

ABSTRACT: BACKGROUND: Ancestry informative markers (AIMs) are a type of genetic marker that is informative for tracing the ancestral ethnicity of individuals. Application of AIMs has gained substantial attention in population genetics, forensic sciences, and medical genetics. Single nucleotide polymorphisms (SNPs), the materials of AIMs, are useful for classifying individuals from distinct continental origins but cannot discriminate individuals with subtle genetic differences from closely related ancestral lineages. Proof-of-principle studies have shown that gene expression (GE) also is a heritable human variation that exhibits differential intensity distributions among ethnic groups. GE supplies ethnic information supplemental to SNPs; this motivated us to integrate SNP and GE markers to construct AIM panels with a reduced number of required markers and provide high accuracy in ancestry inference. Few studies in the literature have considered GE in this aspect, and none have integrated SNP and GE markers to aid classification of samples from closely related ethnic populations. RESULTS: We integrated a forward variable selection procedure into flexible discriminant analysis to identify key SNP and/or GE markers with the highest cross-validation prediction accuracy. By analyzing genome-wide SNP and/or GE markers in 210 independent samples from four ethnic groups in the HapMap II Project, we found that average testing accuracies for a majority of classification analyses were quite high, except for SNP-only analyses that were performed to discern study samples containing individuals from two close Asian populations. The average testing accuracies ranged from 0.53 to 0.79 for SNP-only analyses and increased to around 0.90 when GE markers were integrated together with SNP markers for the classification of samples from closely related Asian populations. Compared to GE-only analyses, integrative analyses of SNP and GE markers showed comparable testing accuracies and a reduced number of selected markers in AIM panels. CONCLUSIONS: Integrative analysis of SNP and GE markers provides high-accuracy and/or cost-effective classification results for assigning samples from closely related or distantly related ancestral lineages to their original ancestral populations. User-friendly BIASLESS (Biomarkers Identification and Samples Subdivision) software was developed as an efficient tool for selecting key SNP and/or GE markers and then building models for sample subdivision. BIASLESS was programmed in R and R-GUI and is available online at http://www.stat.sinica.edu.tw/hsinchou/genetics/prediction/BIASLESS.htm.     

Genome-wide Insights into the Patterns and Determinants of Fine-Scale Population Structure in Humans

Studying genomic patterns of human population structure provides important insights into human evolutionary history and the relationship among populations, and it has significant practical implications for disease-gene mapping. Here we describe a principal component (PC)-based approach to studying intracontinental population structure in humans, identify the underlying markers mediating the observed patterns of fine-scale population structure, and infer the predominating evolutionary forces shaping local population structure. We applied this methodology to a data set of 650K SNPs genotyped in 944 unrelated individuals from 52 populations and demonstrate that, although typical PC analyses focus on the top axes of variation, substantial information about population structure is contained in lower-ranked PCs. We identified 18 significant PCs, some of which distinguish individual populations. In addition to visually representing sample clusters in PC biplots, we estimated the set of all SNPs significantly correlated with each of the most informative axes of variation. These polymorphisms, unlike ancestry-informative markers (AIMs), constitute a much larger set of loci that drive genomic signatures of population structure. The genome-wide distribution of these significantly correlated markers can largely be accounted for by the stochastic effects of genetic drift, although significant clustering does occur in genomic regions that have been previously implicated as targets of recent adaptive evolution.     

Estimating genome-wide heterozygosity: effects of demographic history and marker type

Heterozygosity–fitness correlations (HFCs) are often used to link individual genetic variation to differences in fitness. However, most studies examining HFCs find weak or no correlations. Here, we derive broad theoretical predictions about how many loci are needed to adequately measure genomic heterozygosity assuming different levels of identity disequilibrium (ID), a proxy for inbreeding. We then evaluate the expected ability to detect HFCs using an empirical data set of 200 microsatellites and 412 single nucleotide polymorphisms (SNPs) genotyped in two populations of bighorn sheep (Ovis canadensis), with different demographic histories. In both populations, heterozygosity was significantly correlated across marker types, although the strength of the correlation was weaker in a native population compared with one founded via translocation and later supplemented with additional individuals. Despite being bi-allelic, SNPs had similar correlations to genome-wide heterozygosity as microsatellites in both populations. For both marker types, this association became stronger and less variable as more markers were considered. Both populations had significant levels of ID; however, estimates were an order of magnitude lower in the native population. As with heterozygosity, SNPs performed similarly to microsatellites, and precision and accuracy of the estimates of ID increased as more loci were considered. Although dependent on the demographic history of the population considered, these results illustrate that genome-wide heterozygosity, and therefore HFCs, are best measured by a large number of markers, a feat now more realistically accomplished with SNPs than microsatellites.     

Effects of natural selection on interpopulation divergence at polymorphic sites in human protein-coding Loci

To develop new strategies for searching for genetic associations with complex human diseases, we analyzed 2784 single-nucleotide polymorphisms (SNPs) in 396 protein-coding genes involved in biological processes relevant to cancer and other complex diseases, with respect to gene diversity within samples of individuals representing the three major historic human populations (African, European, and Asian) and with respect to interpopulation genetic distance. Reduced levels of both intrapopulation gene diversity and interpopulation genetic distance were seen in the case of SNPs located within the 5'-UTR and at nonsynonymous SNPs, causing radical changes to protein structure. Reduction of gene diversity at SNP loci in these categories was evidence of purifying selection acting at these sites, which in turn causes a reduction in interpopulation divergence. By contrast, a small number of SNP sites in these categories revealed unusually high genetic distances between the two most diverged populations (African and Asian); these loci may have historically been subject to divergent selection pressures.