全基因组关联研究通路分析方法现状

全基因组关联研究(genome-wide association study, GWAS)自2005年首次发表以来已不断增进人们对疾病遗传机制的认识,结合系统生物学并改进统计分析方法是对GWAS数据进行深度挖掘的重要途径。通路分析(pathway analysis)将GWAS所检测的遗传变异根据一定的生物学含义组合为集合进行分析,有利于发现对疾病单独效应小却在通路中相互关联的遗传变异,更有利于进行生物学解释。当前通路分析在GWAS数据上已有较为广泛的应用并取得初步成果。与此同时,通路分析的统计方法仍在不断发展。本文旨在介绍现有直接以SNP为对象的GWAS通路分析算法,根据方法中是否采用核函数分为非核算法和核算法两大类,其中非核算法主要包括基因功能富集分析(gene set enrichment analysis, GSEA)和分层贝叶斯优取(hierarchical Bayes prioritization, HBP),核算法包括线性核(linear kernel, LIN)、状态认证核(identity-by-status kernel, IBS)和尺度不变核(powered exponential kernel)。通过介绍这些方法的计算原理和优缺点,以期为新算法的构建提供更好的思路,为GWAS领域研究方法的选择提供参考。     

肺结核全基因组关联研究进展

肺结核是由结核分枝杆菌感染引起的一类古老但仍对人类造成巨大影响的传染性疾病。到目前为止, 肺结核依然是由单一病原菌导致死亡人数最多的疾病, 并且随着耐药菌株的出现而呈现死灰复燃之势。近几年, 肺结核全基因组关联研究在世界范围内取得了阶段性成果, 发现了与肺结核相关联的遗传易感位点和区域, 使肺结核的遗传学研究进入了一个崭新的阶段, 为后续肺结核的早期和综合防治提供了重要线索。然而, 由于人群遗传结构差异和宿主/病原体相互作用, 与其他复杂疾病相比, 肺结核全基因组关联研究依旧面临重重困难, 进展缓慢。文章对不同人群肺结核全基因组关联研究及其验证进行综述, 并系统阐述了目前研究中存在的困难及可能的应对策略。     

冠心病全基因组关联研究进展

近年来全基因组关联研究在世界范围内发展迅猛,研究者应用全基因组关联研究策略发现了一系列疾病的相关基因或变异,将疾病的基因组研究推向一个新的阶段。冠心病是一种由环境因素和遗传因素共同作用导致的复杂疾病,且是世界范围内死亡和致残的首要原因之一,世界各地的研究者应用此策略发现了候选基因关联研究未曾发现的多个冠心病相关易感区域。文章对近年来世界范围内针对冠心病的全基因组关联研究取得的重要进展进行简要总结,然后就现阶段全基因组关联研究所面临的挑战以及对未来研究的发展趋势进行分析阐述,为进一步探究冠心病的遗传机制提供指导。     

细菌全基因组关联研究的方法与应用

随着测序技术的发展和全基因组序列的不断积累,全基因组关联研究(genome-wide association study, GWAS)在人类复杂疾病研究中取得了丰硕成果,10余年间发现了数以万计的疾病风险因子。同样,GWAS也为探索细菌表型的遗传机制提供了新的工具。自2013年第一项细菌GWAS(bacterial GWAS, BGWAS)工作发表以来,目前已有10多项相关研究报道,分别揭示了细菌宿主适应性、耐药性及毒力等表型的遗传机制,极大加深了人们对细菌遗传、进化及传播等方面的认识。本文对目前BGWAS的研究方法、应用成果及存在的问题进行了总结,并对BGWAS的研究前景进行了展望,旨在为微生物学领域开展BGWAS研究提供参考。     

全基因组关联研究现状

在过去的5年中, 全基因组关联研究(Genome-wide association study, GWAS)方法已被证明是研究复杂疾病和性状遗传易感变异的一种有效手段。目前, 各国科学家在多种复杂疾病和性状中开展了大量的GWAS, 对肿瘤、糖尿病、心脏病、神经精神疾病、自身免疫及免疫相关疾病等复杂疾病以及一些常见性状(如身高、体重、血脂、色素等)的遗传易感基因研究取得了重大成果。截止到2010年9月11日, 运用GWAS开展了对近200种复杂疾病/性状的研究, 发现了3 000多个疾病相关的遗传变异。文章就GWAS的发展及其在复杂疾病/性状中的应用做一综述。     

A genome-wide association study identified new variants associated with mathematical abilities in Chinese children

Mathematical ability is moderately heritable, and it is a complex trait which can be evaluated in several different categories. A few genetic studies have been published on general mathematical ability. However, no genetic study focused on specific mathematical ability categories. In this study, we separately performed genome-wide association studies on 11 mathematical ability categories in 1146 students from Chinese elementary schools. We identified seven genome-wide significant single nucleotide polymorphisms (SNPs) with strong linkage disequilibrium among each other (all r² > 0.8) associated with mathematical reasoning ability (top SNP: rs34034296, p = 2.01 × 10⁻⁸, nearest gene: CUB and Sushi multiple domains 3, CSMD3). We replicated one SNP (rs133885) from 585 SNPs previously reported to be associated with general mathematical ability associated with division ability in our data (p = 1.053 × 10⁻⁵). In the gene- and gene-set enrichment analysis by MAGMA, we found three significant enrichments of associations with three mathematical ability categories for three genes (LINGO2, OAS1 and HECTD1). We also observed four significant enrichments of associations with four mathematical ability categories for three gene sets. Our results suggest new candidate genetic loci for the genetics of mathematical ability.     

桃基因组及全基因组关/联分析研究进展

桃(Prunus persica [L.] Batsch)是蔷薇科重要的核果类果树, 适应性强, 栽培范围广, 果实口感好, 深受消费者喜欢。提高桃果实品质及增加抗病、抗虫性一直是桃遗传育种者关注的焦点。文章对近年来桃遗传分子标记连锁图谱和物理图谱构建、分子标记开发应用、全基因组和转录组测序工作中所取得的最新成果进行综述, 同时阐述了高密度SNP芯片标记技术在桃以及其它作物上所开展的全基因组关联分析应用实例, 为桃进一步开展全基因组关联分析, 挖掘目标性状QTLs以及高效育种选择标记提供理论基础     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状,随着平衡育种理念的提出和发展,繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展,全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

原发性高血压全基因组关联研究进展

原发性高血压是一种由遗传与环境因素共同导致的复杂疾病,具有高度的遗传异质性。自2007年首个高血压全基因组关联研究(Genome-wide association studies,GWAS)报道以来,许多GWAS相继开展。文章首先对2007年1月至2011年9月期间报道的24篇血压/高血压易感基因的GWAS按人种与染色体位置对其结果进行汇总,经统计位点rs17249754、rs1378942和rs11191548报道频数最多。其次介绍了GWAS方法学的研究进展,包括选择高质量的数量表型和选择多阶段研究设计来增加研究发现阳性关联的机会。统计分析方面,除强调了已经报道过的多重比较和重复(验证)研究等问题外,文章还介绍了通过Meta分析对GWAS数据进行深度发掘,并应用基因型填补法对缺失数据进行填补可以提高全基因组遗传标记的覆盖率的方法。尽管GWAS发现了许多我们未知的基因与疾病表型的关联,为了解高血压的发病机制提供了更多线索,但是目前GWAS发现的血压/高血压相关变异多为对人群血压的影响极其微弱的常见变异。因此今后的研究中可加强深度功能学研究对易感基因精细定位和外显子组测序技术的应用,结合GWAS的成果进行生物信息学通路分析和表观遗传学机制研究等,逐步揭示高血压的遗传机制。     

GWAS研究大肠杆菌和金黄色葡萄球菌种间互作进化机制

【目的】通过实验室培养模拟自然环境微生物相互作用,进而找到影响细菌基因型和表型的基因。【方法】将大肠杆菌和金黄色葡萄球菌在实验室条件下进行单独培养和两两混合培养并连续转接,通过得到的数量表型与最大生长速率表型做全基因组关联分析(GWAS),对得到的与表型相关的SNP进行注释与分析。【结果】162个SNP位点影响到大肠杆菌原始菌株与共培养菌株的生长,36个SNP位点影响大肠杆菌菌株在单独培养和共同培养的生长。总共有85个SNP位点影响金黄色葡萄球菌的原始菌株与单独培养。其中5个基因在之前文献中已有报道。对影响不同时间点细菌数量变化形状的SNP位点进行功能注释,大肠杆菌中有706个与生长性能相关。金黄色葡萄球菌中,129个和不同的生长性能相关。大肠杆菌SNP位点的13个基因在之前的研究中已有报道。【结论】混合培养和单独培养都检测到与生长相关的显著基因,本研究表明了GWAS在研究细菌互作进化机制方面的潜力。     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状, 随着平衡育种理念的提出和发展, 繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展, 全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

基于高通量测序的全基因组关联研究策略

全基因组关联研究（Genome-wide association study, GWAS）是人类复杂疾病研究的重要组成部分之一,在群体水平检测全基因组范围的遗传变异与可观测性状间的遗传关联。传统的GWAS是以芯片（Array）技术获得高密度的遗传变异,尽管硕果累累,但也存在不少问题。如：所谓的“缺失的遗传力”,即利用关联分析检测达到全基因组水平显著的遗传变异位点只能解释小部分遗传力;在某些性状上不同研究的结果一致性较弱;显著关联的遗传变异位点的功能较难解释等。高通量测序技术,也称第二代测序（Next-generation sequencing, NGS）技术,可以快速、准确地产出高通量的变异位点数据,为解决以上问题提供了可行的方案。基于NGS技术的GWAS方法（NGS-GWAS）,可在一定程度上弥补传统GWAS的不足。文章对NGS-GWAS策略和方法进行了系统性调研,提出了目前较为可行的NGS-GWAS的实施策略和方法,并对NGS-GWAS如何应用于个体化医疗（Personalized medicine, PM）进行了展望。     

Pathway analysis of a genome-wide association study in schizophrenia

Objective

The aim of this study was to identify the candidate single nucleotide polymorphisms (SNPs) and candidate mechanisms that contribute to schizophrenia susceptibility and to generate a SNP to gene to pathway hypothesis using an analytical pathway-based approach.

Methods

We used schizophrenia GWAS data of the genotypes of 660,259 SNPs in 1378 controls and 1351 cases of European descent after quality control filtering. ICSNPathway (Identify candidate Causal SNPs and Pathways) analysis was applied to the schizophrenia GWAS dataset. The first stage involved the pre-selection of candidate SNPs by linkage disequilibrium analysis and the functional SNP annotation of the most significant SNPs found. The second stage involved the annotation of biological mechanisms for the pre-selected candidate SNPs using improved-gene set enrichment analysis.

Results

ICSNPathway analysis identified fifteen candidate SNPs, ten candidate pathways, and nine hypothetical biological mechanisms. The most strongly associated potential pathways were as follows. First, rs1644731 and rs1644730 to RDH8 to estrogen biosynthetic process (p < 0.001, FDR < 0.001). The genes involved in this pathway are RDH8 and HSD3B1 (p < 0.05). All-trans-retinol dehydrogenase (RDH8) is a visual cycle enzyme that reduces all-trans-retinal to all-trans-retinol in the presence of NADPH. The chemical reactions and pathways involved result in the formation of estrogens, which are C18 steroid hormones that can stimulate the development of female sexual characteristics. Second, rs1146031 to ACVR1 to mesoderm formation and activin binding (p < 0.001, FDR = 0.032, 0.034). Two of 15 candidate genes are known genes associated with schizophrenia: KCNQ2 and APOL2. One of the 10 candidate pathways, estrogen biosynthetic process, is known to be associated with schizophrenia (p < 0.001, FDR < 0.001). However, 13 of candidate genes (RDH8, ACVR1, PSMD9, KCNAB1, SLC17A3, ARCN1, COG7, STAB2, LRPAP1, STAB1, CXCL16, COL4A4, EXOSC3) and 9 of candidate pathways were novel.

Conclusion

By applying ICSNPathway analysis to schizophrenia GWAS data, we identified candidate SNPs, genes like KCNQ2 and APOL2 and pathways involving the estrogen biosynthetic process may contribute to schizophrenia susceptibility. Further analyses are needed to validate the results of this analysis.     

A genome-wide association study reveals that the 2-oxoglutarate/malate translocator mediates seed vigor in rice

Seed vigor is an important trait for the direct seeding of rice (Oryza sativa L.). In this study, we examined the genetic architecture of variation in the germination rate using a diverse panel of rice accessions. Four quantitative trait loci for germination rate were identified using a genome-wide association study during early germination. One candidate gene, encoding the 2-oxoglutarate/malate translocator (OsOMT), was validated for qGR11. Disruption of this gene (Osomt mutants) reduced seed vigor, including seed germination and seedling growth, in rice. Functional analysis revealed that OsOMT influences seed vigor mainly by modulating amino acid levels and glycolysis and tricarboxylic acid cycle processes. The levels of most amino acids, including the Glu family (Glu, Pro, Arg, and GABA), Asp family (Asp, Thr, Lys, Ile, and Met), Ser family (Ser, Gly, and Cys), and others (His, Ala, Leu, and Val), were significantly reduced in the mature grains and the early germinating seeds of Osomt mutants compared to wild type (WT). The glucose and soluble sugar contents, as well as adenosine triphosphate levels, were significantly decreased in germinating seeds of Osomt mutants compared to WT. These results provide important insights into the role of OsOMT in seed vigor in rice.     

全基因组关联研究的深度分析策略

2005年至今,全基因组关联研究(Genome-wide association study,GWAS)发现了大量复杂疾病/性状相关变异。近来,科学家们关注的焦点又集中在了如何利用GWAS数据进行深入分析,期待发现更多复杂疾病/性状的易感基因。一些新的策略和方法已经被尝试应用到复杂疾病/性状GWAS的后续研究中,例如深入分析GWAS数据;鉴定新的复杂疾病/性状易感基因/位点;国际合作和Meta分析;易感区域精细定位及测序;多种疾病共同易感基因研究;以及基因型填补,基于通路的关联分析,基因-基因、基因-环境交互作用和上位研究等。这些策略和方法的应用弥补了经典GWAS的一些不足之处,进一步推动了人类对复杂疾病/性状遗传机制的认识。文章对上述研究的策略、方法以及所面临的问题和挑战进行了综述,为读者描绘了GWAS后期工作的一个简要框架。     

A genome-wide significant association on chromosome 15 for congenital entropion in Swiss White Alpine sheep

Entropion is a known congenital disorder in sheep presumed to be heritable but no causative genetic variant has been reported. Affected lambs show a variable inward rolling of the lower eyelids leading to blindness in severe cases. In Switzerland, the Swiss White Alpine (SWA) breed showed a significantly higher prevalence for entropion than other breeds. A GWAS using 150 SWA sheep (90 affected lambs and 60 controls), based on 600k SNP data, revealed a genome-wide significant signal on chromosome 15. The 0.2 Mb associated region contains functional candidate genes, SMTNL1 and CTNND1. Pathogenic variants in human CTNND1 cause blepharocheilodontic syndrome 2, a rare disorder including eyelid anomalies, and SMTNL1 regulates contraction and relaxation of skeletal and smooth muscle. WGS of a single entropion-affected lamb revealed two private missense variants in SMTNL1 and CTNND1. Subsequent genotyping of both variants in 231 phenotyped SWA sheep was performed. The SMTNL1 variant p.(Asp452Asn) affects an evolutionary conserved residue within an important domain and represents a rare allele, which occurred also in controls. The p.(Glu943Lys) variant in CTNND1 represents a common variant unlikely to cause entropion as the mutant allele occurred more frequently in non-affected sheep. Therefore, we propose that these protein-changing variants are unlikely to explain the phenotype. Additionally, WGS of three further disconcordant pairs of full siblings was carried out but revealed no obvious causative variant. Finally, we conclude that entropion represents a more complex disease caused by different non-coding regulatory variants.     

Prioritization of SNPs for genome-wide association studies using an interaction model of genetic variation,gene expression,and trait variation

The identification of true causal loci to unravel the statistical evidence of genotype-phenotype correlations and the biological relevance of selected single-nucleotide polymorphisms (SNPs) is a challenging issue in genome-wide association studies (GWAS). Here, we introduced a novel method for the prioritization of SNPs based on p-values from GWAS. The method uses functional evidence from populations, including phenotype-associated gene expressions. Based on the concept of genetic interactions, such as perturbation of gene expression by genetic variation, phenotype and gene expression related SNPs were prioritized by adjusting the p-values of SNPs. We applied our method to GWAS data related to drug-induced cytotoxicity. Then, we prioritized loci that potentially play a role in druginduced cytotoxicity. By generating an interaction model, our approach allowed us not only to identify causal loci, but also to find intermediate nodes that regulate the flow of information among causal loci, perturbed gene expression, and resulting phenotypic variation.