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1.

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.  相似文献   

2.
The success stories of identifying genes in Mendelian disorders have stimulated research that aims at identifying the genetic determinants in complex disorders, in which both genetics, environment and chance affect the pathogenetic processes. This review summarizes the brief history and lessons learned from genetic analysis of complex disorders and outlines some landscapes ahead for medical research.  相似文献   

3.
4.
The human face is a heritable surface with many complex sensory organs. In recent years, many genetic loci associated with facial features have been reported in different populations, yet there is a lack of studies on the Han Chinese population. Here, we report a genome-wide association study of 3 D normal human faces of 2,659 Han Chinese with autosegment phenotypes of facial morphology. We identify singlenucleotide polymorphisms(SNPs) encompassing four genomic regions showing significant associations with different facial regions, including SNPs in DENND1 B associated with the chin, SNPs among PISRT1 associated with eyes, SNPs between DCHS2 and SFRP2 associated with the nose, and SNPs in VPS13 B associated with the nose. We replicate 24 SNPs from previously reported genetic loci in different populations, whose candidate genes are DCHS2, SUPT3 H, HOXD1, SOX9, PAX3, and EDAR. These results provide a more comprehensive understanding of the genetic basis of variation in human facial morphology.  相似文献   

5.
    
Pathway analysis, also known as gene-set enrichment analysis, is a multilocus analytic strategy that integrates a priori, biological knowledge into the statistical analysis of high-throughput genetics data. Originally developed for the studies of gene expression data, it has become a powerful analytic procedure for indepth mining of genome-wide genetic variation data. Astonishing discoveries were made in the past years,uncovering genes and biological mechanisms underlying common and complex disorders. However, as massive amounts of diverse functional genomics data accrue, there is a pressing need for newer generations of pathway analysis methods that can utilize multiple layers of high-throughput genomics data. In this review, we provide an intellectual foundation of this powerful analytic strategy, as well as an update of the state-of-the-art in recent method developments. The goal of this review is threefold:(1) introduce the motivation and basic steps of pathway analysis for genome-wide genetic variation data;(2) review the merits and the shortcomings of classic and newly emerging integrative pathway analysis tools; and(3)discuss remaining challenges and future directions for further method developments.  相似文献   

6.

Background

Chronic bronchitis (CB) is one of the classic phenotypes of COPD. The aims of our study were to investigate genetic variants associated with COPD subjects with CB relative to smokers with normal spirometry, and to assess for genetic differences between subjects with CB and without CB within the COPD population.

Methods

We analyzed data from current and former smokers from three cohorts: the COPDGene Study; GenKOLS (Bergen, Norway); and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). CB was defined as having a cough productive of phlegm on most days for at least 3 consecutive months per year for at least 2 consecutive years. CB COPD cases were defined as having both CB and at least moderate COPD based on spirometry. Our primary analysis used smokers with normal spirometry as controls; secondary analysis was performed using COPD subjects without CB as controls. Genotyping was performed on Illumina platforms; results were summarized using fixed-effect meta-analysis.

Results

For CB COPD relative to smoking controls, we identified a new genome-wide significant locus on chromosome 11p15.5 (rs34391416, OR = 1.93, P = 4.99 × 10-8) as well as significant associations of known COPD SNPs within FAM13A. In addition, a GWAS of CB relative to those without CB within COPD subjects showed suggestive evidence for association on 1q23.3 (rs114931935, OR = 1.88, P = 4.99 × 10-7).

Conclusions

We found genome-wide significant associations with CB COPD on 4q22.1 (FAM13A) and 11p15.5 (EFCAB4A, CHID1 and AP2A2), and a locus associated with CB within COPD subjects on 1q23.3 (RPL31P11 and ATF6). This study provides further evidence that genetic variants may contribute to phenotypic heterogeneity of COPD.

Trial registration

ClinicalTrials.gov NCT00608764, NCT00292552

Electronic supplementary material

The online version of this article (doi:10.1186/s12931-014-0113-2) contains supplementary material, which is available to authorized users.  相似文献   

7.
玉米是世界上种植面积最大、总产量最高的粮食作物,其籽粒重量的70%来自于淀粉。淀粉不仅是人类及其他动物的主要能量来源,同时也是化工等行业的重要原料。利用拟南芥、水稻等模式植物,淀粉合成相关基因克隆与功能研究已取得较多进展。近年来,随着玉米淀粉含量相关遗传学研究的深入开展,通过数量性状位点(quantitative trait locus mapping,QTL)定位、全基因组关联分析(genome-wide association study, GWAS)及各种组学分析方法,发现了较多新的与淀粉含量相关的遗传位点及候选基因,但是尚缺乏归纳总结。综述了玉米籽粒淀粉合成与调控研究进展,对玉米籽粒淀粉含量相关的QTL和基因进行汇总和分析,通过构建一致性物理图谱,提炼玉米籽粒淀粉含量遗传定位热点区间,这为进一步解析玉米籽粒淀粉合成与代谢相关基因的功能提供参考,并为分子标记辅助育种提供遗传资源。  相似文献   

8.
    
Alfalfa(Medicago sativa L.) is the most important legume forage crop worldwide with high nutritional value and yield.For a long time,the breeding of alfalfa was hampered by lacking reliable information on the autotetraploid genome and molecular markers linked to important agronomic traits.We herein reported the de novo assembly of the allele-aware chromosome-level genome of Zhongmu-4,a cultivar widely cultivated in China,and a comprehensive database of genomic variations based on resequencing of...  相似文献   

9.
Some case-control genome-wide association studies (CCGWASs) select promising single nucleotide polymorphisms (SNPs) by ranking corresponding p-values, rather than by applying the same p-value threshold to each SNP. For such a study, we define the detection probability (DP) for a specific disease-associated SNP as the probability that the SNP will be "T-selected," namely have one of the top T largest chi-square values (or smallest p-values) for trend tests of association. The corresponding proportion positive (PP) is the fraction of selected SNPs that are true disease-associated SNPs. We study DP and PP analytically and via simulations, both for fixed and for random effects models of genetic risk, that allow for heterogeneity in genetic risk. DP increases with genetic effect size and case-control sample size and decreases with the number of nondisease-associated SNPs, mainly through the ratio of T to N, the total number of SNPs. We show that DP increases very slowly with T, and the increment in DP per unit increase in T declines rapidly with T. DP is also diminished if the number of true disease SNPs exceeds T. For a genetic odds ratio per minor disease allele of 1.2 or less, even a CCGWAS with 1000 cases and 1000 controls requires T to be impractically large to achieve an acceptable DP, leading to PP values so low as to make the study futile and misleading. We further calculate the sample size of the initial CCGWAS that is required to minimize the total cost of a research program that also includes follow-up studies to examine the T-selected SNPs. A large initial CCGWAS is desirable if genetic effects are small or if the cost of a follow-up study is large.  相似文献   

10.
The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.  相似文献   

11.
Distinct enterotypes have been observed in the human gut but little is known about the genetic basis of the microbiome. Moreover, it is not clear how many genetic differences exist between enterotypes within or between populations. In this study, both the 16S rRNA gene and the metagenomes of the gut microbiota were sequenced from 48 Han Chinese, 48 Kazaks, and 96 Uyghurs, and taxonomies were assigned after de novo assembly. Single nucleotide polymorphisms were also identified by referring to data from the Human Microbiome Project. Systematic analysis of the gut communities in terms of their abundance and genetic composition was also performed, together with a genome-wide association study of the host genomes. The gut microbiota of 192 subjects was clearly classified into two enterotypes (Bacteroides and Prevotella). Interestingly, both enterotypes showed a clear genetic differentiation in terms of their functional catalogue of genes, especially for genes involved in amino acid and carbohydrate metabolism. In addition, several differentiated genera and genes were found among the three populations. Notably, one human variant (rs878394) was identified that showed significant association with the abundance of Prevotella, which is linked to LYPLAL1, a gene associated with body fat distribution, the waist-hip ratio and insulin sensitivity. Taken together, considerable differentiation was observed in gut microbes between enterotypes and among populations that was reflected in both the taxonomic composition and the genetic makeup of their functional genes, which could have been influenced by a variety of factors, such as diet and host genetic variation.  相似文献   

12.
13.

Background

The domestic dog is a rich resource for mapping the genetic components of phenotypic variation due to its unique population history involving strong artificial selection. Genome-wide association studies have revealed a number of chromosomal regions where genetic variation associates with morphological characters that typify dog breeds. A region on chromosome 10 is among those with the highest levels of genetic differentiation between dog breeds and is associated with body mass and ear morphology, a common motif of animal domestication. We characterised variation in this region to uncover haplotype structure and identify candidate functional variants.

Results

We first identified SNPs that strongly associate with body mass and ear type by comparing sequence variation in a 3 Mb region between 19 breeds with a variety of phenotypes. We next genotyped a subset of 123 candidate SNPs in 288 samples from 46 breeds to identify the variants most highly associated with phenotype and infer haplotype structure. A cluster of SNPs that associate strongly with the drop ear phenotype is located within a narrow interval downstream of the gene MSRB3, which is involved in human hearing. These SNPs are in strong genetic linkage with another set of variants that correlate with body mass within the gene HMGA2, which affects human height. In addition we find evidence that this region has been under selection during dog domestication, and identify a cluster of SNPs within MSRB3 that are highly differentiated between dogs and wolves.

Conclusions

We characterise genetically linked variants that potentially influence ear type and body mass in dog breeds, both key traits that have been modified by selective breeding that may also be important for domestication. The finding that variants on long haplotypes have effects on more than one trait suggests that genetic linkage can be an important determinant of the phenotypic response to selection in domestic animals.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1702-2) contains supplementary material, which is available to authorized users.  相似文献   

14.
    

Background

Emerging studies demonstrate that single nucleotide polymorphisms (SNPs) resided in the microRNA recognition element seed sites (MRESSs) in 3′UTR of mRNAs are putative biomarkers for human diseases and cancers. However, exhaustively experimental validation for the causality of MRESS SNPs is impractical. Therefore bioinformatics have been introduced to predict causal MRESS SNPs. Genome-wide association study (GWAS) provides a way to detect susceptibility of millions of SNPs simultaneously by taking linkage disequilibrium (LD) into account, but the multiple-testing corrections implemented to suppress false positive rate always sacrificed the sensitivity. In our study, we proposed a method to identify candidate causal MRESS SNPs from 12 GWAS datasets without performing multiple-testing corrections. Alternatively, we used biological context to ensure credibility of the selected SNPs.

Results

In 11 out of the 12 GWAS datasets, MRESS SNPs were over-represented in SNPs with p-value ≤ 0.05 (odds ratio (OR) ranged from 1.1 to 2.4). Moreover, host genes of susceptible MRESS SNPs in each of the 11 GWAS dataset shared biological context with reported causal genes. There were 286 MRESS SNPs identified by our method, while only 13 SNPs were identified by multiple-testing corrections with a given threshold of 1 × 10−5, which is a common cutoff used in GWAS. 27 out of the 286 candidate SNPs have been reported to be deleterious while only 2 out of 13 multiple-testing corrected SNPs were documented in PubMed. MicroRNA-mRNA interactions affected by the 286 candidate SNPs were likely to present negatively correlated expression. These SNPs introduced greater alternation of binding free energy than other MRESS SNPs, especially when grouping by haplotypes (4210 vs. 4105 cal/mol by mean, 9781 vs. 8521 cal/mol by mean, respectively).

Conclusions

MRESS SNPs are promising disease biomarkers in multiple GWAS datasets. The method of integrating GWAS p-value and biological context is stable and effective for selecting candidate causal MRESS SNPs, it reduces the loss of sensitivity compared to multiple-testing corrections. The 286 candidate causal MRESS SNPs provide researchers a credible source to initialize their design of experimental validations in the future.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-669) contains supplementary material, which is available to authorized users.  相似文献   

15.
Chen  Jiahua; Chen  Zehua 《Biometrika》2008,95(3):759-771
The ordinary Bayesian information criterion is too liberal formodel selection when the model space is large. In this paper,we re-examine the Bayesian paradigm for model selection andpropose an extended family of Bayesian information criteria,which take into account both the number of unknown parametersand the complexity of the model space. Their consistency isestablished, in particular allowing the number of covariatesto increase to infinity with the sample size. Their performancein various situations is evaluated by simulation studies. Itis demonstrated that the extended Bayesian information criteriaincur a small loss in the positive selection rate but tightlycontrol the false discovery rate, a desirable property in manyapplications. The extended Bayesian information criteria areextremely useful for variable selection in problems with a moderatesample size but with a huge number of covariates, especiallyin genome-wide association studies, which are now an activearea in genetics research.  相似文献   

16.
    
To demonstrate the loci that relate to high-density lipoprotein cholesterol (HDL-C) levels and genetic sex heterogeneity, we enrolled 41,526 participants aged between 30 and 70 years old from the Taiwan Biobank in a genome-wide association study. We applied the Manhattan plot to display the p-values estimated for the relationships between loci and low HDL-C. A total of 160 variants were significantly associated with low HDL-C. The genotype TT of rs1364422 located in the KLF14 gene has 1.30 (95% CI=1.20 - 1.42) times the risk for low-HDL compared to genotype CC in females (log(-p) =8.98). Moreover, the genes APOC1, APOE, PVRL2, and TOMM40 were associated significantly with low-HDL-C in males only. Excluding the variants with high linkage disequilibrium, we revealed the rs429358 located in APOE as the major genetic variant for lowering HDL-C, in which genotype CT has 1.24 (95% CI= 1.16 - 1.32) times the risk. In addition, we also examine 12 genes related to HDL-C in both sexes, including LPL, ABCA1, APOA5, BUD13, ZPR1, ALDH1A2, LIPC, CETP, HERPUD1, LIPG, ANGPTL8, and DOCK6. In conclusion, low-HDL-C is a genetic and sex-specific phenotype, and we discovered that the APOE and KLF14 are specific to low-HDL-C for men and women, respectively.  相似文献   

17.
林木的分子病理学研究长期以来落后于农业作物病理学。随着高通量测序技术的问世,林木的分子病理学研究迎来了一个崭新的时代。从2006年至今,杨树、云杉等重要森林树种的全基因组测序相继完成,这为全面解析林木的抗病过程提供了遗传背景。同时,转录组学和全基因组关联分析的应用使得人们能快速地积累大量的数据,从而为揭示林木和病原菌之间的分子互作机制奠定了基础。近两年来CRISPR/Cas9基因编辑等分子生物学技术创新不断。高效的分子生物学技术结合基因组学研究有利于林木育种的研究。以下阐述了林木对抗病原菌入侵的生理机制,综合论述了近十年来基因组学和转录组学研究在木本植物分子病理学方面所取得的成果,总结了分子生物学技术在林木抗病领域的研究成果,分析了存在的问题和未来发展的趋势,以期为林木抗病育种提供参考。  相似文献   

18.
    
Previous studies have reported that some important loci are missed in single-locus genome-wide association studies (GWAS), especially because of the large phenotypic error in field experiments. To solve this issue, multi-locus GWAS methods have been recommended. However, only a few software packages for multi-locus GWAS are available. Therefore, we developed an R software named mrMLM v4.0.2. This software integrates mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO methods developed by our lab. There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs. In addition, the graphical user interface software mrMLM.GUI v4.0.2, built upon Shiny, is also available. To confirm the correctness of the aforementioned programs, all the methods in mrMLM v4.0.2 and three widely-used methods were used to analyze real and simulated datasets. The results confirm the superior performance of mrMLM v4.0.2 to other methods currently available. False positive rates are effectively controlled, albeit with a less stringent significance threshold. mrMLM v4.0.2 is publicly available at BioCode (https://bigd.big.ac.cn/biocode/tools/BT007077) or R (https://cran.r-project.org/web/packages/mrMLM.GUI/index.html) as an open-source software.  相似文献   

19.
株高和穗位高是玉米重要育种性状,直接影响植株的养分利用效率及抗倒伏性,进而影响玉米产量。玉米株高和穗位高属于典型数量性状,目前通过数量性状位点(quantitative trait loci mapping,QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法已挖掘到较多相关遗传位点,通过QTL精细定位及利用突变体克隆了一些调控株高和穗位高关键基因。但是由于各研究组所利用的群体类型和大小、标记类型和密度以及统计方法不同,所鉴定QTL差异较大,单个研究难以揭示玉米株高和穗位高遗传结构。早期QTL定位的结果多以遗传距离来展示,不同时期GWAS研究所使用参考基因组版本不同,这进一步增加了借鉴和利用前人研究结果的难度。首次将目前已鉴定株高和穗位高遗传定位信息统一锚定至玉米自交系B73参考基因组V4版本,构建了株高和穗位高性状定位的一致性图谱,并鉴定出可被多个独立研究定位的热点区间。进一步对已克隆玉米株高和穗位高调控基因进行总结与分类,揭示株高和穗位高性状调控机制,对深度解析株高和穗位高遗传结构、指导基因克隆和利用分子标记辅助选择优化玉米株高和穗位高性状均具有重要意义。  相似文献   

20.
    
Genome-wide association studies(GWAS) have identified thousands of genomic loci associated with complex diseases and traits, including cancer. The vast majority of common traitassociated variants identified via GWAS fall in non-coding regions of the genome, posing a challenge in elucidating the causal variants, genes, and mechanisms involved. Expression quantitative trait locus(e QTL) and other molecular QTL studies have been valuable resources in identifying candidate causal genes from GWAS loc...  相似文献   

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