精神分裂症相关基因的预测——基于大规模数据的整合分析

精神分裂症(Schizophrenia)是一种遗传性复杂、多基因相关的疾病,对其相关基因的研究一直都是疾病基因研究的热点和前沿,也是遗传学领域的难题.随着目前各种组学数据(Omics Data)的产生,全基因组关联研究(GWAS)中和精神分裂症相关的单核苷酸多态位点(SNP)越来越多的公布于学界,整合这些大规模数据并利用生物信息学模型预测精神分裂症相关基因能为进一步翔实探究致病或相关基因提供基因库的富集和优选.本文首先运用已被证明预测表现优秀的随机森林模型(Random Forests)预测精神分裂症的相关基因,然后用全基因组关联研究得到的相关基因的SNP位点进行验证及进一步筛选候选基因.结果随机森林预测模型得到33个精神分裂症候选基因,其中10个基因具有58个SNP位点是精神分裂症GWAS中的显著性SNP位点,因而这10个基因为优选的精神分裂症候选基因,文献查询结果表明这10个优选相关基因与精神分裂症有密切联系.     

应用 COMT 基因 SNP 位点鉴别拉布拉多和金毛猎犬胆量行为的研究

摘要:目的 检测拉布拉多和金毛猎犬儿茶酚-O-甲基转移酶( Catechol-O-methyltransferase,COMT)基因 SNP 位点的多态性,并统计分析 SNP 位点的基因型及单倍型与犬胆量行为间的关联性,以期为工作犬培训的前期筛选提供有效的遗传学分子标记。 方法 选取 91 只拉布拉多和 27 只金毛猎犬,共计 118 只,采用犬胆量评估( dog courage assessment,DCA)测试方法对犬的胆量行为进行评估,用高分辨率熔解曲线法( high resolution melting,HRM) 对该118 只犬的 COMT 基因的 4 个 SNP 位点:-1 666 bp C>G、c. 39 A>G、c. 216 G>A 和 c. 482 G>A 进行基因型鉴定,应用SPSS 19. 0 和 PHASE 2. 1 软件统计分析 4 个 SNP 位点的基因型和单倍型与犬胆量行为之间的相关性。 结果 拉布拉多和金毛猎犬的品种、性别和年龄与犬的胆量行为之间没有显著关联性( P>0. 05) 。 COMT 基因的 4 个 SNP 位点的基因型与拉布拉多和金毛猎犬的胆量行为之间存在显著相关性( P< 0. 01) 。 COMT 基因 4 个 SNP 位点的单倍型与拉布拉多和金毛猎犬的胆小性情显著相关( P<0. 01) ,并且 c. 216 G>A 和 c. 482 G>A 位点的 A 等位基因在犬的胆小行为上起主导作用。 结论 COMT 基因的 4 个 SNP 位点的基因型和单倍型与拉布拉多和金毛猎犬的胆量行为之间存在显著相关性,提示 COMT 基因对犬的胆量行为具有显著的影响,可作为胆小犬早期鉴定的有效遗传学分子标记。     

含有前列腺癌风险性SNPrs1741708的潜在增强子座位在前列腺癌中功能与机制的研究

前列腺癌(Prostate Cancer,PCa)是老年男性最常见的恶性肿瘤之一.全基因组关联研究(Genome wide Association Studies,GWAS)发现SNP(Single Nucleotide Polymorphism)位点rs1741708与前列腺癌高风险性相关.表观遗传学标志物和荧光素酶报告子研究证实含有该风险性位点的染色体区段是等位基因特异性的增强子元件.敲除风险性增强子会导致细胞迁移能力减弱.利用Capture-C揭示该增强子在全基因组范围内的互作基因座位,结合风险性增强子敲除后基因表达的改变,鉴定出一些该增强子的直接靶基因.初步的Rescue研究发现,在敲除细胞中过表达靶基因IKZF3后,细胞迁移能力得到部分恢复,提示IKZF3是含有SNP rs1741708的风险性增强子影响肿瘤恶性进展的下游靶基因之一.     

基因组预测中先验分布的两种超参数设定策略比较

基因组选择是通过全基因组的标记信息估计出个体的基因组育种值并加以选择的育种方法.主要围绕最佳线性无偏预测(BLUP)和贝叶斯方法展开.这些方法均在某种先验假设下进行,因此需要对先验分布的参数进行设定.依据设定先验超参数的原理,探讨了对单核苷酸多态性(SNP)基因型进行与不进行标准化两种策略下先验超参数的设定方法,并利用QTLMAS2012的模拟数据,分别计算了7种预测方法(岭回归BLUP(RRBLUP)、BayesA、BayesB、BayesCπ、快速BayesB(FBayesB),快速混合正态分布(FMixP)和基于马尔科夫链-蒙特卡洛算法的MixP(简称MMixP))在2种策略下的基因组育种值.结果显示:当采用同一种预测方法,对SNP基因型进行标准化处理与否不影响基因组育种值估计结果.但由于对基因型进行标准化处理在方法上更具有通用性,并可以突出效应大的SNP位点,故建议进行SNP效应值估计前,先将SNP基因型标准化,再设定先验分布的参数值.     

中国小麦周8425B/中国春RIL群体成株抗叶锈基因的QTL定位

为确定小麦叶锈病抗病基因的QTL检测及定位,找到能与抗病基因紧密连锁的分子标记,以小麦品种周8425B,中国春及其杂交获得的244个F_(2∶8) RIL群体为试验材料,分别于2014～2015年在河北保定和河南周口进行了田间叶锈病病害严重度调查,获得了群体的表型数据,利用SNP标记和SSR标记进行基因分型,得到了群体基因型数据,运用软件Joinmap和QTL Ici Mapping 3.1进行连锁作图和QTL定位。结果找到2个QTL位点,分别位于2B,7D染色体上。     

全基因组关联研究中整合分析统计方法的比较（英文）

全基因组关联研究(GWAS)已经发现许多与复杂的人类特征以及疾病有关的遗传变异.由于伦理和隐私问题,个体水平的基因型和表现型数据往往不容易被获取.相比之下,GWAS汇总统计正变得广泛可用.由于整合分析结合了多个GWAS,可以大幅增加样本量,从而增加检测到遗传变异的统计功效.因而,许多GWAS整合分析的统计方法被提了出来.随着GWAS整合分析统计方法的增加,研究人员需要一些有用的指导为实际数据的分析应用选择合适的统计方法.该文评估了GWAS中一些现有的整合分析方法的性能,使用了全面的模拟研究来比较这些方法的效能,并指出了每种方法的优缺点.     

前列腺癌风险性SNP rs55958994相关的增强子座位促进lncRNA HOTAIR表达增强肿瘤细胞迁移能力

长链非编码RNA(lncRNA)在恶性肿瘤发生发展中发挥重要的作用,其中lncRNA HOTAIR已经被证实能够促进多重肿瘤的转移.前期研究通过全基因组关联研究(GWAS)发现,12号染色体长臂13区13带(12q13.13)的SNP位点rs55958994是前列腺癌独立风险因子,通过生物信息学分析发现含有该风险性SNP的染色体座位是一个潜在的增强子元件,在22Rv1细胞系中敲除该增强子座位发现肿瘤细胞的转移侵袭能力明显降低;采用Capture-C实验结合基因表达谱分析发现该增强子元件通过染色质长距离相互作用调节lncRNA HOTAIR的表达;进一步采用细胞分子生物学实验证实HOTAIR是该风险性增强子影响肿瘤进展的关键基因之一.     

BMP7基因多态对大白猪生长性状的影响

目的为了筛查猪BMP7基因SNP位点及分析其对猪生长性状的影响。方法通过PCR产物测序确定BMP7基因外显子上的5个潜在多态位点,用sequenom法对实验猪群进行基因分型并开展基因型与猪生长性状的关联分析。结果在BMP7基因5个潜在SNP位点中检测确定了2个SNP位点:A83509G和G84966A,且均属错义突变。A83509G位点AA型校正达100 kg日龄显著低于AG型和GG型(P0.05),GG型校正达100 kg眼肌面积显著高于AG型(P0.05); G84966A位点GG型校正达100 kg日龄和达100 kg眼肌面积都显著高于AA型(P0.05);在A83509G和G84966A位点单倍型中,AGGA、AAAA型个体校正达100 kg日龄显著低于AGGG基因型个体(P 0.05); AGGA基因型个体校正达100 kg眼肌面积显著高于AGAA基因型个体(P0.05)。结论 A83509G、G84966A变异位点对大白猪眼肌面积及生长速度具有显著影响,可作为猪生长性状选择的潜在分子标记。     

VNTR技术用于大理地区结核分枝杆菌基因分型的研究

目的:应用数目可变串联重复序列(VNTR)分子分型技术,对大理地区60株肺结核临床分离株进行分型研究,探讨大理地区菌株DNA多态性及基因型特征。方法:采用VNTR分子分型技术对60株结核分枝杆菌3个VNTR位点进行检测,应用Quantity one软件和BioNumerics 6.6软件进行聚类分析。结果:60株结核分枝杆菌可以分为4个基因群(Ⅰ群、Ⅱ群、Ⅲ群、Ⅳ群),28个基因型。Ⅰ群占15.0%,含有5个基因型,Ⅱ群占31.7%,含有8个基因型,Ⅲ群占40.0%,含有11个基因型,Ⅳ群占13.3%,含有4个基因型。结论:大理地区的结核分枝杆菌存在基因多态性,其主要流行群为Ⅲ群。     

新疆维吾尔族人TNFβ-804基因多态性与乙型肝炎易感性的相关性研究

目的：研究TNF-β基因单核苷酸多态性（SNP）804位点与新疆地区维吾尔族人乙型肝炎之间的关系。方法：用套式PCR（nested PCR）和等位基因特异性PCR（allele一speciicfic PCR,AS-PCR）法,对120例乙肝患者和120例正常对照者TNF-β基因SNP804多态性位点进行基因分型。结果：SNP804多态性位点C/C基因型和C/A＋AA基因型频率在病例组为77%和23%,正常对照组为88%和12%,两组间基因型和等位基因频率分布差异有显著性（p〈0.05）。结论：TNF-β804多态性位点与新疆维吾尔族人乙肝有明显相关性。     

Genome-Wide Interaction-Based Association of Human Diseases—A Survey

Genome-Wide Association Studies（GWASs） aim to identify genetic variants that are associated with disease by assaying and analyzing hundreds of thousands of Single Nucleotide Polymorphisms（SNPs）. Although traditional single-locus statistical approaches have been standardized and led to many interesting findings, a substantial number of recent GWASs indicate that for most disorders, the individual SNPs explain only a small fraction of the genetic causes. Consequently, exploring multi-SNPs interactions in the hope of discovering more significant associations has attracted more attentions. Due to the huge search space for complicated multilocus interactions, many fast and effective methods have recently been proposed for detecting disease-associated epistatic interactions using GWAS data. In this paper, we provide a critical review and comparison of eight popular methods, i.e., BOOST, TEAM, epi Forest, EDCF, SNPHarvester, epi MODE, MECPM, and MIC, which are used for detecting gene-gene interactions among genetic loci. In views of the assumption model on the data and searching strategies, we divide the methods into seven categories. Moreover, the evaluation methodologies,including detecting powers, disease models for simulation, resources of real GWAS data, and the control of false discover rate, are elaborated as references for new approach developers. At the end of the paper, we summarize the methods and discuss the future directions in genome-wide association studies for detecting epistatic interactions.     

Pathway-based analysis for genome-wide association studies of schizophrenia to provide new insight in schizophrenia study

Schizophrenia (SZ) is an inheritable complex mental disease. There have been several genome-wide association studies (GWASs) of SZ to identify novel genetic susceptibility factors. To further interpret SZ GWASs, pathway-based analysis (PBA), which considers the combined effect of variants and identifies pathways associated with traits, provides a feasible solution to discover the biological function and mechanism of SZ. Furthermore, to investigate the common pathways between SZ and bipolar disorder (BD) wil...     

随机试验设计中缺失值插补方法研究

随机化区组设计中经常会碰到缺失数据,处理此类缺失数据目前有4种方法：删除缺失数据法、均值插补法、公式插补法和Yate’s插补法。4种方法的优劣是值得研究的一个问题,拟用模拟研究的方法对此4种方法进行比较。首先随机产生一个4x5的随机区组设计,令缺失值的个数m=l,…,6;其次对每个n遍历所有缺失值位置可能的组合,在每一个缺失值位置的组合下,分别研究4种方法线性回归的标准误差、可决系数和复可决系数。最后模拟研究的结果证实Yate’s插补方法是这4种方法中表现最好的一个,实例研究的结果也证实了模拟研究的结论。     

浅论我国公平责任的立法规制及其改善

我国《侵权责任法》虽已颁布，但民法学界对侵权责任的一些基本问题实际上尚未进行深入探究和充分研讨。在欠缺充分学理积累的情况下仓促制定的《侵权责任法》乃至今后将要制定的民法典无异于先天不足的早产儿。对侵权责任制度而言具有根本性意义的首先是归责原则问题。我国民法学界在20世纪80年代末与20世纪90年代前期对该问题曾有过激烈论争，但此后逐渐归于沉寂。近两年来随着《侵权责任法》的起草和颁布，出现了大量关于侵权责任的研究成果，但涉及归责原则的则相对较少。笔者拟对传统的过错责任原则及我国民法中的“公平责任原则”予以检讨，并尝试对侵权行为的归责提出立法设想。     

基于灰色关联分析的类中心缺失值填补方法

真实数据集中含有缺失值,许多数据分析技术不能直接应用到不完整数据上,且缺失值的存在会明显地降低算法的有效性,缺失数据处理是一个不可缺少的数据预处理过程,因此提出了一个基于统计度量的缺失值填补算法,名为灰色类中心缺失值填补(GCCMVI)方法,利用数据点的类中心和标准差来填补缺失值,此外,通过比较阈值和实例与类中心间相关性的大小关系,决定是否加上(减去)标准差,灰色关联分析用来计算相关性,在缺失值被填补后,得到的完整的数据集用来训练支持向量机(SVM)分类器.在三种类型不同的数据集上进行比较,以分类精度,填补效果,填补时间作为评估准则来衡量算法的有效性.实验结果表明,所提出的算法显著地提高了分类精度和填补效果.     

A second generation human haplotype map of over 3.1 million SNPs

We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.     

ARC/INFOR~接受Surfer图文数据的实现

数据是地理信息系统 (GIS)应用的核心。现实世界的数据具有普遍的多样性 ,关于 GIS接受不同数据的研究已成为当前 GIS研究中的一个难点和热点。本文根据通用 GIS工具软件 ARC/INFO接受外部空间数据的方式和图形分析软件 Surfer的数据格式特征 ,运用特定的处理方法实现了由 Surfer格式数据向 ARC/ INFO矢量格式数据 (Coverage)的转换 ,使 ARC/ INFO接受外部数据格式的范围拓宽 ,数据处理能力增强。     

An SNP map of human chromosome 22

The human genome sequence will provide a reference for measuring DNA sequence variation in human populations. Sequence variants are responsible for the genetic component of individuality, including complex characteristics such as disease susceptibility and drug response. Most sequence variants are single nucleotide polymorphisms (SNPs), where two alternate bases occur at one position. Comparison of any two genomes reveals around 1 SNP per kilobase. A sufficiently dense map of SNPs would allow the detection of sequence variants responsible for particular characteristics on the basis that they are associated with a specific SNP allele. Here we have evaluated large-scale sequencing approaches to obtaining SNPs, and have constructed a map of 2,730 SNPs on human chromosome 22. Most of the SNPs are within 25 kilobases of a transcribed exon, and are valuable for association studies. We have scaled up the process, detecting over 65,000 SNPs in the genome as part of The SNP Consortium programme, which is on target to build a map of 1 SNP every 5 kilobases that is integrated with the human genome sequence and that is freely available in the public domain.     

Genome-wide association study identifies novel breast cancer susceptibility loci

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2 > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P < 10(-7)). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P < 0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.     

TNF receptor 1 genetic risk mirrors outcome of anti-TNF therapy in multiple sclerosis

Although there has been much success in identifying genetic variants associated with common diseases using genome-wide association studies (GWAS), it has been difficult to demonstrate which variants are causal and what role they have in disease. Moreover, the modest contribution that these variants make to disease risk has raised questions regarding their medical relevance. Here we have investigated a single nucleotide polymorphism (SNP) in the TNFRSF1A gene, that encodes tumour necrosis factor receptor 1 (TNFR1), which was discovered through GWAS to be associated with multiple sclerosis (MS), but not with other autoimmune conditions such as rheumatoid arthritis, psoriasis and Crohn’s disease. By analysing MS GWAS data in conjunction with the 1000 Genomes Project data we provide genetic evidence that strongly implicates this SNP, rs1800693, as the causal variant in the TNFRSF1A region. We further substantiate this through functional studies showing that the MS risk allele directs expression of a novel, soluble form of TNFR1 that can block TNF. Importantly, TNF-blocking drugs can promote onset or exacerbation of MS, but they have proven highly efficacious in the treatment of autoimmune diseases for which there is no association with rs1800693. This indicates that the clinical experience with these drugs parallels the disease association of rs1800693, and that the MS-associated TNFR1 variant mimics the effect of TNF-blocking drugs. Hence, our study demonstrates that clinical practice can be informed by comparing GWAS across common autoimmune diseases and by investigating the functional consequences of the disease-associated genetic variation.