新冠肺炎遗传易感基因的研究进展

新型冠状病毒(severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)感染人体后,个体间存在显著不同的新冠肺炎(corona virus disease 2019,COVID-19)临床症状。机体遗传因素在新冠病毒感染后的临床转归过程中发挥重要的作用。以全基因组关联研究(genome-wide association studies, GWAS)为代表的遗传关联研究方法,已成功鉴定了多个与新冠肺炎相关的易感基因,为新冠肺炎防诊治措施的研发提供了理论基础。本文综述了新冠肺炎遗传易感基因的研究进展,包括多种表型、多个人群、多种遗传变异类型的新冠肺炎全基因组关联研究以及易感基因区域的精细定位研究等,旨在为新冠肺炎遗传易感基因的后续研究提供参考。     

中国菜粉蝶线粒体基因组遗传多样性分析

菜粉蝶Pieris rapae是十字花科蔬菜重要的农业害虫。为了深入了解中国菜粉蝶的群体遗传特征,通过高通量测序获取了中国5个群体48头菜粉蝶的线粒体全基因组,并分析了不同群体间的遗传结构与多样性。结果表明：菜粉蝶群体间有较高的线粒体单倍型多样性;相对封闭的山区和盆地地区的核苷酸多样性较低;群体间的平均遗传分化指数（FST）仅0.042,表明不同群体间的遗传分化水平较低,这也暗示了群体间基因交流频繁,推测这与甘蓝等蔬菜频繁运输有关;线粒体进化树和网络图均未形成明显的地理谱系,南北方群体之间没有明显的遗传结构差异;总群体的Tajima''s D和Fu''s Fs值均为负值,且达到了显著水平,这意味着中国地区的菜粉蝶可能经历过群体扩张事件。     

生物信息学分析方法I: 全基因组关联分析概述

全基因组关联分析(GWAS)是动植物复杂性状相关基因定位的常用手段。高通量基因分型技术的应用极大地推动了GWAS的发展。在植物中, 利用GWAS不仅能够以较高的分辨率在全基因组水平鉴定出各种自然群体特定性状相关的基因或区间, 而且可揭示表型变异的遗传架构全景图。目前, 人们利用GWAS分析方法已在拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)、小麦(Triticum aestivum)、玉米(Zea mays)和大豆(Glycine max)等模式植物和重要农作物品系中发掘出与各种性状显著相关的数量性状座位(QTL)及其候选基因位点, 阐明了这些性状的遗传基础, 并为揭示这些性状背后的分子机理提供候选基因, 也为作物高产优质品种的选育提供了理论依据。该文对GWAS的方法、影响因素及数据分析流程进行了详细描述, 以期为相关研究提供参考。     

2型糖尿病易感基因的连锁和关联研究

2型糖尿病（T2DM）是由于胰岛素抵抗和β细胞分泌缺陷导致高血糖的一种复杂多基因疾病。遗传因素在T2DM的发生发展中起着重要的作用,其遗传率估计为70％～80％。鉴定2型糖尿病基因将有助于阐明其发病机制,发展更好的诊断、预防和治疗策略。2型糖尿病易感基因的鉴定方法主要有候选基因关联研究和全基因组连锁分析。有3种类型的候选基因：功能候选基因、图位候选基因和表达候选基因。虽然许多候选基因与T2DM的关联分析已经进行,但多数都没有得到一致的重复,过氧化物酶体增殖物激活受-γ,体和β-细胞ATP敏感性钾通道基因是目前最好重复的基因。迄今为止,T2DM的全基因组扫描已在20多个不同的群体中进行,包括欧洲人、美国白人、墨西哥裔美国人、美国本地印度人、非洲裔美国人和亚洲人,这些研究鉴定了一些与T2DM相关的QTLs区域。与T2DM显著和证实连锁的区域包括1q25、2q37．3q28、3p24、6q22、8p23、10q26、12q24、18p11、20q13等,与T2DM提示连锁的区域有1q42、2p21、2q24、4q34、5q13、5q31、7q32、9p24、9q21、10p14、11p13、11q13、12q15、14q23、20p12、Xq23等。鉴定这些区域的T2DMQTLs基因及其作用机制是未来的主要挑战。把DNA微阵列和蛋白质组学技术结合起来应用于传统的连锁分析和关联研究,研究基因-基因间、基因-环境间的互作和多个基因对T2DM的加性效应和综合作用,进一步加强国际协作,T2DM的遗传机制可望在不远的将来得到阐明。本文总结了2型糖尿病基因鉴定的现状,重点在一些得到重复的区域和未来的展望。     

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。     

长江中游鳊群体的遗传多样性

采用线粒体DNA(mt DNA)细胞色素b基因(cytb)和控制区序列,分析长江中游宜都、沙市、燕窝、团风等4个产卵场鳊种群的遗传多样性和遗传结构。结果表明:长江中游鳊群体cytb序列共检出82个多态位点,86种单倍型,平均单倍型多样性指数(Hd)和核苷酸多样性指数(Pi)分别为0.930和0.00244;控制区序列共检出变异位点46个,单倍型76种,Hd指数和Pi指数分别为0.972和0.00505;构建的单倍型网络结构和分子方差分析(AMOVA)显示,4个群体的遗传变异绝大部分来自群体内部,群体间无显著遗传分化;群体间的分化指数(FST)、平均基因流(Nm)和平均K2-P遗传距离均表明,4个鳊地理群体间存在广泛的基因交流,未发生明显群体遗传分化;中性检验表明,鳊历史上发生了群体扩张,扩张时间在第四纪冰期后期。     

肖四海湖野生和人工放流鳜群体遗传结构分析

采用微卫星标记研究天然封闭型水体肖四海内鳜放流群体与野生群体的遗传差异,试图从分子水平探讨人工增殖放流群体与野生群体遗传结构的差异。结果表明:鳜两个群体在10对微卫星座位共发现有50个等位基因。其中,放流群体发现有22个等位基因,野生群体发现37个等位基因;通过He和PIC统计发现,野生群体遗传多样性明显高于放流增殖鳜,野生鳜群体表现出更丰富的遗传多样性;由杂合度检验可以看出,两个群体都呈现杂合过剩现象,经哈代-温伯格平衡检验,显示两个群体均显著偏离哈代-温伯格平衡(P0.001),属于连锁不平衡群体;群体间的FST检验,可以看出群体间的FST高于0.25,反映遗传变异主要存在于群体间,而不是群体内部,这充分反映近交及瓶颈效应会引起养殖群体遗传结构的改变,从而导致群体间的遗传分化。       

中国人群肝癌的易感基因研究

以单核苷酸多态性（single nucleotide polymorphism,SNP）为遗传标记的遗传关联研究是近年来鉴定复杂疾病易感基因的主要策略之一.尤其是新近发展成熟的全基因组关联研究（genome-wide association study,GWAS）,已被公认是行之有效的系统搜寻重大疾病易感基因的研究方法.军事医学科学院与国内同行合作开展的HBV相关肝癌GWAS结果表明,1p36.22的UBE4B-KIF1B-PGD区域是一个全新的肝癌易感基因区域,证明了遗传易感性在肝癌发生发展中的病因学意义.肝癌易感基因的发现,不仅为深入阐明肝癌的发生机制开辟了新的研究方向,而且为肝癌的风险预测和早期预警研究提供了理论依据;同时,也为后续开发新型的治疗药物奠定了基础.     

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。     

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。     

Unifying candidate gene and GWAS Approaches in Asthma

The first genome wide association study (GWAS) for childhood asthma identified a novel major susceptibility locus on chromosome 17q21 harboring the ORMDL3 gene, but the role of previous asthma candidate genes was not specifically analyzed in this GWAS. We systematically identified 89 SNPs in 14 candidate genes previously associated with asthma in >3 independent study populations. We re-genotyped 39 SNPs in these genes not covered by GWAS performed in 703 asthmatics and 658 reference children. Genotyping data were compared to imputation data derived from Illumina HumanHap300 chip genotyping. Results were combined to analyze 566 SNPs covering all 14 candidate gene loci. Genotyped polymorphisms in ADAM33, GSTP1 and VDR showed effects with p-values <0.0035 (corrected for multiple testing). Combining genotyping and imputation, polymorphisms in DPP10, EDN1, IL12B, IL13, IL4, IL4R and TNF showed associations at a significance level between p = 0.05 and p = 0.0035. These data indicate that (a) GWAS coverage is insufficient for many asthma candidate genes, (b) imputation based on these data is reliable but incomplete, and (c) SNPs in three previously identified asthma candidate genes replicate in our GWAS population with significance after correction for multiple testing in 14 genes.     

Whole-genome sequence analysis reveals differences in population management and selection of European low-input pig breeds

Background

A major concern in conservation genetics is to maintain the genetic diversity of populations. Genetic variation in livestock species is threatened by the progressive marginalisation of local breeds in benefit of high-output pigs worldwide. We used high-density SNP and re-sequencing data to assess genetic diversity of local pig breeds from Europe. In addition, we re-sequenced pigs from commercial breeds to identify potential candidate mutations responsible for phenotypic divergence among these groups of breeds.

Results

Our results point out some local breeds with low genetic diversity, whose genome shows a high proportion of regions of homozygosis (>50%) and that harbour a large number of potentially damaging mutations. We also observed a high correlation between genetic diversity estimates using high-density SNP data and Next Generation Sequencing data (r = 0.96 at individual level). The study of non-synonymous SNPs that were fixed in commercial breeds and also in any local breed, but with different allele, revealed 99 non-synonymous SNPs affecting 65 genes. Candidate mutations that may underlie differences in the adaptation to the environment were exemplified by the genes AZGP1 and TAS2R40. We also observed that highly productive breeds may have lost advantageous genotypes within genes involve in immune response – e.g. IL12RB2 and STAB1–, probably as a result of strong artificial in the intensive production systems in pig.

Conclusions

The high correlation between genetic diversity computed with the 60K SNP and whole genome re-sequence data indicates that the Porcine 60K SNP Beadchip provides reliable estimates of genomic diversity in European pig populations despite the expected bias. Moreover, this analysis gave insights for strategies to the genetic characterization of local breeds. The comparison between re-sequenced local pigs and re-sequenced commercial pigs made it possible to report candidate mutations to be responsible for phenotypic divergence among those groups of breeds. This study highlights the importance of low input breeds as a valuable genetic reservoir for the pig production industry. However, the high levels of ROHs, inbreeding and potentially damaging mutations emphasize the importance of the genetic characterization of local breeds to preserve their genomic variability.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-601) contains supplementary material, which is available to authorized users.     

Validation of Type 2 Diabetes Risk Variants Identified by Genome-Wide Association Studies in Han Chinese Population: A Replication Study and Meta-Analysis

Background

Several genome-wide association studies (GWAS) involving European populations have successfully identified risk genetic variants associated with type 2 diabetes mellitus (T2DM). However, the effects conferred by these variants in Han Chinese population have not yet been fully elucidated.

Methods

We analyzed the effects of 24 risk genetic variants with reported associations from European GWAS in 3,040 Han Chinese subjects in Taiwan (including 1,520 T2DM cases and 1,520 controls). The discriminative power of the prediction models with and without genotype scores was compared. We further meta-analyzed the association of these variants with T2DM by pooling all candidate-gene association studies conducted in Han Chinese.

Results

Five risk variants in IGF2BP2 (rs4402960, rs1470579), CDKAL1 (rs10946398), SLC30A8 (rs13266634), and HHEX (rs1111875) genes were nominally associated with T2DM in our samples. The odds ratio was 2.22 (95% confidence interval, 1.81-2.73, P<0.0001) for subjects with the highest genetic score quartile (score>34) as compared with subjects with the lowest quartile (score<29). The incoporation of genotype score into the predictive model increased the C-statistics from 0.627 to 0.657 (P<0.0001). These estimates are very close to those observed in European populations. Gene-environment interaction analysis showed a significant interaction between rs13266634 in SLC30A8 gene and age on T2DM risk (P<0.0001). Further meta-analysis pooling 20 studies in Han Chinese confirmed the association of 10 genetic variants in IGF2BP2, CDKAL1, JAZF1, SCL30A8, HHEX, TCF7L2, EXT2, and FTO genes with T2DM. The effect sizes conferred by these risk variants in Han Chinese were similar to those observed in Europeans but the allele frequencies differ substantially between two populations.

Conclusion

We confirmed the association of 10 variants identified by European GWAS with T2DM in Han Chinese population. The incorporation of genotype scores into the prediction model led to a small but significant improvement in T2DM prediction.     

The spatial genetic structure of cytoplasmic (cpDNA) and nuclear (allozyme) markers within and among populations of the gynodioecious Thymus vulgaris (Labiatae) in southern France

Recent advances in molecular biology have allowed the development of techniques to contrast spatial differentiation in nuclear and cytoplasmic genes and thus provide important data on relative levels of gene flow by pollen and seed in higher plants. In this paper, we compare the spatial structure of nuclear (allozymes) and cytoplasmic (cpDNA) genes among populations of the gynodioecious Thymus vulgaris in southern France. Based on a combination of three restriction enzymes (CfoI, EcoRV, and PstI), eight chlorotypes (combination of three restriction enzyme patterns revealed by Southern hybridization of Beta vulgaris cpDNA) were identified in the 13 studied populations. One chlorotype was particularly abundant and was detected in nearly all populations. Only one chlorotype was specific to a single population. Up to four different chlorotypes were observed in some populations. An FST of 0.238 (P < 0.002) for cpDNA haplotypes indicates spatial structure of cytoplasmic genes among the studied populations. Similar patterns were found within a single young population (CAB) structured in patches and surrounded by a continuous cover of T. vulgaris where the FST is 0.546 (P < 0.002). No significant correlation between sex and chlorotype nor between cpDNA diversity and female frequency was detected. Allozyme markers showed markedly less spatial structure (FST = 0.021 among populations and 0.019 in the CAB population, P < 0.001). This difference between cpDNA and nuclear allozyme markers suggests that pollen dispersal is more important than seed dispersal both among and within populations.     

Nuclear gene sequences and DNA variation of Cryptomeria japonica samples from the postglacial period

Genomic DNA was extracted from heartwood blocks of six Cryptomeria japonica individuals that had been buried (in an area now covered by rice fields) for about 3600 years. Attempts were made to determine the sequences of five nuclear genes following polymerase chain reaction amplification, using previously obtained C. japonica expressed sequence tag (EST) information. We detected 15 nucleotide substitutions and four insertion/deletions (indels) in a partial GapC gene sequence among 13 individuals of the buried and an extant population, which allowed us to estimate the extent of DNA variation within the buried populations, and the level of genetic differentiation between the buried population and the extant population growing in a neighbouring area. For the entire haplotypes of the GapC region, pi and theta nucleotide diversity estimates were 0.0063 and 0.0010, respectively, when both populations were included, while corresponding figures for the buried population alone were 0.0009 and 0.0017. Estimates of DNA divergence statistics (dXY = 0.0062, dA = 0.0005, FST = 0.0832 and KST = 0.0935) suggest that differentiation between the two populations was not great. However, permutation tests gave FST and KST values rejecting the null hypothesis (that populations were not differentiated) at the 5% and 1% probability levels, respectively. The significant genetic differentiation between the two populations was mainly caused by differences in haplotype diversity. The significant level of haplotype diversity in the extant population compared to the buried population might be the result of gene flow from neighbouring artificial forests. Alternatively, it is possible that we failed to detect all the DNA variation in the buried population because of clonal growth in the buried population.     

An analysis of genetic variation in natural populations of Sticherus flabellatus [R. Br. (St John)] using amplified fragment length polymorphism (AFLP) markers

Amplified fragment length polymorphisms (AFLPs) were used to characterize the genetic diversity within and among natural populations of Sticherus flabellatus. Eight populations within the Sydney region of New South Wales, Australia were surveyed using 11 primer combinations. A total of 1108 reproducible bands were detected of which 469 (42%) were polymorphic. FST estimates averaged over all polymorphic loci indicated that significant genomic differentiation occurs among populations (average = 0.783). Genetic diversity within populations was assessed according to average heterozygosity (H) and percentage polymorphic loci (P) per population. Within-population diversity ranged from H = 0.12 and P = 33.69 to H = 0.04 and P = 15.99. Analysis of genetic similarity among populations suggested that the eight populations studied fall into two groups of four populations, based on population size and the condition of the habitat. Phenetic analysis (AMOVA) indicated that genetic variation is greater among populations (74.34%) than within populations (25.66%). These findings suggest that the breeding system of S. flabellatus is predominantly inbreeding, with genetic diversity maintained by occasional outcrossing in larger populations. The results presented in this study could provide evidence to support the proposal to protect natural stands of S. flabellatus, which has implications for the Australian horticulture industry.     

Huge populations and old species of Costa Rican and Panamanian dirt frogs inferred from mitochondrial and nuclear gene sequences

Molecular genetic data were used to investigate population sizes and ages of Eleutherodactylus (Anura: Leptodactylidae), a species-rich group of small leaf-litter frogs endemic to Central America. Population genetic structure and divergence was investigated for four closely related species surveyed across nine localities in Costa Rica and Panama. DNA sequence data were collected from a mitochondrial gene (ND2) and a nuclear gene (c-myc). Phylogenetic analyses yielded concordant results between loci, with reciprocal monophyly of mitochondrial DNA haplotypes for all species and of c-myc haplotypes for three of the four species. Estimates of genetic differentiation among populations (FST) based upon mitochondrial data were always higher than nuclear-based FST estimates, even after correcting for the expected fourfold lower effective population size (Ne) of the mitochondrial genome. Comparing within-population variation and the relative mutation rates of the two genes revealed that the Ne of the mitochondrial genome was 15-fold lower than the estimate of the nuclear genome based on c-myc. Nuclear FST estimates were approximately 0 for the most proximal pairs of populations, but ranged from 0.5 to 1.0 for all other pairs, even within the same nominal species. The nuclear locus yielded estimates of Ne within localities on the order of 105. This value is two to three orders of magnitude larger than any previous Ne estimate from frogs, but is nonetheless consistent with published demographic data. Applying a molecular clock model suggested that morphologically indistinguishable populations within one species may be 107 years old. These results demonstrate that even a geologically young and dynamic region of the tropics can support very old lineages that harbour great levels of genetic diversity within populations. The association of high nucleotide diversity within populations, large divergence between populations, and high species diversity is also discussed in light of neutral community models.     

Deep resequencing identifies candidate functional genes in leprosy GWAS loci

Leprosy is the second most prevalent mycobacterial disease globally. Despite the existence of an effective therapy, leprosy incidence has consistently remained above 200,000 cases per year since 2010. Numerous host genetic factors have been identified for leprosy that contribute to the persistently high case numbers. In the past decade, genetic epidemiology approaches, including genome-wide association studies (GWAS), identified more than 30 loci contributing to leprosy susceptibility. However, GWAS loci commonly encompass multiple genes, which poses a challenge to define causal candidates for each locus. To address this problem, we hypothesized that genes contributing to leprosy susceptibility differ in their frequencies of rare protein-altering variants between cases and controls. Using deep resequencing we assessed protein-coding variants for 34 genes located in GWAS or linkage loci in 555 Vietnamese leprosy cases and 500 healthy controls. We observed 234 nonsynonymous mutations in the targeted genes. A significant depletion of protein-altering variants was detected for the IL18R1 and BCL10 genes in leprosy cases. The IL18R1 gene is clustered with IL18RAP and IL1RL1 in the leprosy GWAS locus on chromosome 2q12.1. Moreover, in a recent GWAS we identified an HLA-independent signal of association with leprosy on chromosome 6p21. Here, we report amino acid changes in the CDSN and PSORS1C2 genes depleted in leprosy cases, indicating them as candidate genes in the chromosome 6p21 locus. Our results show that deep resequencing can identify leprosy candidate susceptibility genes that had been missed by classic linkage and association approaches.     

A hierarchical Bayesian model for next-generation population genomics

The demography of populations and natural selection shape genetic variation across the genome and understanding the genomic consequences of these evolutionary processes is a fundamental aim of population genetics. We have developed a hierarchical Bayesian model to quantify genome-wide population structure and identify candidate genetic regions affected by selection. This model improves on existing methods by accounting for stochastic sampling of sequences inherent in next-generation sequencing (with pooled or indexed individual samples) and by incorporating genetic distances among haplotypes in measures of genetic differentiation. Using simulations we demonstrate that this model has a low false-positive rate for classifying neutral genetic regions as selected genes (i.e., Φ(ST) outliers), but can detect recent selective sweeps, particularly when genetic regions in multiple populations are affected by selection. Nonetheless, selection affecting just a single population was difficult to detect and resulted in a high false-negative rate under certain conditions. We applied the Bayesian model to two large sets of human population genetic data. We found evidence of widespread positive and balancing selection among worldwide human populations, including many genetic regions previously thought to be under selection. Additionally, we identified novel candidate genes for selection, several of which have been linked to human diseases. This model will facilitate the population genetic analysis of a wide range of organisms on the basis of next-generation sequence data.