A common SNP of MCPH1 is associated with cranial volume variation in Chinese population

Microcephaly (MCPH) genes are informative in understanding the genetics and evolution of human brain volume. MCPH1 and abnormal spindle-like MCPH associated (ASPM) are the two known MCPH causing genes that were suggested undergone recent positive selectio

Genome-wide SNP and haplotype analyses reveal a rich history underlying dog domestication

Advances in genome technology have facilitated a new understanding of the historical and genetic processes crucial to rapid phenotypic evolution under domestication(1,2). To understand the process of dog diversification better, we conducted an extensive genome-wide survey of more than 48,000 single nucleotide polymorphisms in dogs and their wild progenitor, the grey wolf. Here we show that dog breeds share a higher proportion of multi-locus haplotypes unique to grey wolves from the Middle East, indicating that they are a dominant source of genetic diversity for dogs rather than wolves from east Asia, as suggested by mitochondrial DNA sequence data(3). Furthermore, we find a surprising correspondence between genetic and phenotypic/functional breed groupings but there are exceptions that suggest phenotypic diversification depended in part on the repeated crossing of individuals with novel phenotypes. Our results show that Middle Eastern wolves were a critical source of genome diversity, although interbreeding with local wolf populations clearly occurred elsewhere in the early history of specific lineages. More recently, the evolution of modern dog breeds seems to have been an iterative process that drew on a limited genetic toolkit to create remarkable phenotypic diversity.

长牡蛎SNP标记的开发及多态性检测

长牡蛎是重要的经济养殖贝类，良种化、抗逆性状及快速生长个体的培育是长牡蛎养殖业得以持续发展的基础。目前飞速发展的分子标记辅助育种技术为优良品种的快速培育提供了理论基础和实践经验。本研究以长牡蛎为主要研究材料，探讨了长牡蛎SNP标记的筛选和多态性评价。 本研究利用已有长牡蛎EST库中的序列进行单核苷酸多态（SNP）标记开发。通过对长牡蛎（Crassostrea gigas）已有的EST序列数据库检索，经过序列聚类和拼接得到EST簇4548个，含有不少于4条EST序列的簇共1079个，经过进一步设置筛选条件，整理出可供利用的EST簇313个，得到候选SNP位点共计1140个。目前根据候选SNP位点共设计引物82组，通过片段长度差异等位基因特异性PCR（fragment length discrepant allele specific PCR，FLDAS-PCR）的分型方法，在一野生群体中进行检测和验证，结果共有17个SNP候选位点显示多态性，期望杂合度分布区间为0.088至0.506，观测杂合度分布区间为0.091至0.667；通过哈代-温伯格(HW) 平衡、连锁不平衡检验，结果显示除3个SNP位点的差异显著（P值<0.05）,不符合HW平衡之外，其他14个位点没有明显的连锁不平衡。对含有17个SNP的EST的共同序列进行BlastX分析，推测其功能并确定开放阅读框，从而预测17个SNP的性质。 本研究表明对于目前基因组学研究尚处在初级阶段的海洋生物物种，通过基于EST数据库的SNP开发是一条重要途径，可以有效弥补海洋生物基因组学滞后影响SNP标记开发的现状。

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports

BACKGROUND:The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies.METHODS:Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests.RESULTS:The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency [greater than or equal to] 10%, genotype call rate [greater than or equal to] 80%, Hardy-Weinberg equilibrium p-value [greater than or equal to] 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007.CONCLUSION:We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Functional annotation signatures of disease susceptibility loci improve SNP association analysis.

BACKGROUND: Genetic association studies are conducted to discover genetic loci that contribute to an inherited trait, identify the variants behind these associations and ascertain their functional role in determining the phenotype. To date, functional annotations of the genetic variants have rarely played more than an indirect role in assessing evidence for association. Here, we demonstrate how these data can be systematically integrated into an association study's analysis plan. RESULTS: We developed a Bayesian statistical model for the prior probability of phenotype-genotype association that incorporates data from past association studies and publicly available functional annotation data regarding the susceptibility variants under study. The model takes the form of a binary regression of association status on a set of annotation variables whose coefficients were estimated through an analysis of associated SNPs in the GWAS Catalog (GC). The functional predictors examined included measures that have been demonstrated to correlate with the association status of SNPs in the GC and some whose utility in this regard is speculative: summaries of the UCSC Human Genome Browser ENCODE super-track data, dbSNP function class, sequence conservation summaries, proximity to genomic variants in the Database of Genomic Variants and known regulatory elements in the Open Regulatory Annotation database, PolyPhen-2 probabilities and RegulomeDB categories. Because we expected that only a fraction of the annotations would contribute to predicting association, we employed a penalized likelihood method to reduce the impact of non-informative predictors and evaluated the model's ability to predict GC SNPs not used to construct the model. We show that the functional data alone are predictive of a SNP's presence in the GC. Further, using data from a genome-wide study of ovarian cancer, we demonstrate that their use as prior data when testing for association is practical at the genome-wide scale and improves power to detect associations. CONCLUSIONS: We show how diverse functional annotations can be efficiently combined to create 'functional signatures' that predict the a priori odds of a variant's association to a trait and how these signatures can be integrated into a standard genome-wide-scale association analysis, resulting in improved power to detect truly associated variants.

Intragenic SNP haplotypes associated with 84dup18 mutation in TNFRSF11A in four FEO pedigrees suggest three independent origins for this mutation.

Familial expansile osteolysis (FEO) is a rare disorder causing bone dysplasia. The clinical features of FEO include early-onset hearing loss, tooth destruction, and progressive lytic expansion within limb bones causing pain, fracture, and deformity. An 18-bp duplication in the first exon of the TNFRSF11A gene encoding RANK has been previously identified in four FEO pedigrees. Despite having the identical mutation, phenotypic variations among affected individuals of the same and different pedigrees were noted. Another 18-bp duplication, one base proximal to the duplication previously reported, was subsequently found in two unrelated FEO patients. Finally, mutations overlapping with the mutations found in the FEO pedigrees have been found in ESH and early-onset PDB pedigrees. An Iranian FEO pedigree that contains six affected individuals dispersed in three generations has previously been introduced; here, the clinical features of the proband are reported in greater detail, and the genetic defect of the pedigree is presented. Direct sequencing of the entire coding region and upstream and downstream noncoding regions of TNFRSF11A in her DNA revealed the same 18-bp duplication mutation as previously found in the four FEO pedigrees. Additionally, eight sequence variations as compared to the TNFRSF11A reference sequence were identified, and a haplotype linked to the mutation based on these variations was defined. Although the mutation in the Iranian and four of the previously described FEO pedigrees was the same, haplotypes based on the intragenic SNPs suggest that the mutations do not share a common descent.

Targeted genome-wide investigation identifies novel SNP's associated with diabetic nephropathy

Loci contributing to complex disease have been identified by focusing on genome-wide scans utilising non-synonymous single nucleotide polymorphisms (nsSNPs). We employed Illumina’s HNS12 BeadChip (13,917 high-value SNPs) which was specifically designed to capture nsSNPs and ideally complements more dense genome-wide association studies that fail to consider many of these putatively functional variants. The HNS12 panel also includes 870 tag SNPs covering the major histocompatibility region. All individuals genotyped in this study were Caucasians with (cases) and without (controls) diabetic nephropathy. About 449 individuals with type 2 diabetes (203 cases, 246 controls) were genotyped in the initial study. 1,467 individuals with type 1 diabetes (718 cases, 749 controls) were genotyped in the follow up study. 11,152 SNPs were successfully analysed and ranked for association with diabetic nephropathy based on significance (P) values. The top ranked 32 SNPs were subsequently genotyped using MassARRAY iPLEX™ and TaqMan technologies to investigate association of these polymorphisms with nephropathy in individuals with type 1 diabetes. The top ranked nsSNP, rs1543547 (P = 10-5), is located in RAET1L, a major histocompatibility class I-related gene at 6q25.1. Of particular interest, multiple nsSNPs within the top ranked (0.2%) SNPs are within several plausible candidate genes for nephropathy on 3q21.3 and 6p21.3.

Evaluation of a candidate breast cancer associated SNP in ERCC4 as a risk modifier in BRCA1 and BRCA2 mutation carriers. Results from the Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA)

BACKGROUND: In this study we aimed to evaluate the role of a SNP in intron I of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers.

SNP in the genome-wide association study hotspot on chromosome 9p21 confers susceptibility to diabetic nephropathy in type 1 diabetes

AIMS/HYPOTHESIS: Parental type 2 diabetes mellitus increases the risk of diabetic nephropathy in offspring with type 1 diabetes mellitus. Several single nucleotide polymorphisms (SNPs) that predispose to type 2 diabetes mellitus have recently been identified. It is, however, not known whether such SNPs also confer susceptibility to diabetic nephropathy in patients with type 1 diabetes mellitus. METHODS: We genotyped nine SNPs associated with type 2 diabetes mellitus in genome-wide association studies in the Finnish population, and tested for their association with diabetic nephropathy as well as with severe retinopathy and cardiovascular disease in 2,963 patients with type 1 diabetes mellitus. Replication of significant SNPs was sought in 2,980 patients from three other cohorts. RESULTS: In the discovery cohort, rs10811661 near gene CDKN2A/B was associated with diabetic nephropathy. The association remained after robust Bonferroni correction for the total number of tests performed in this study (OR 1.33 [95% CI 1.14, 1.56], p?=?0.00045, p (36tests)?=?0.016). In the meta-analysis, the combined result for diabetic nephropathy was significant, with a fixed effects p value of 0.011 (OR 1.15 [95% CI 1.02, 1.29]). The association was particularly strong when patients with end-stage renal disease were compared with controls (OR 1.35 [95% CI 1.13, 1.60], p?=?0.00038). The same SNP was also associated with severe retinopathy (OR 1.37 [95% CI 1.10, 1.69] p?=?0.0040), but the association did not remain after Bonferroni correction (p (36tests)?=?0.14). None of the other selected SNPs was associated with nephropathy, severe retinopathy or cardiovascular disease. CONCLUSIONS/INTERPRETATION: A SNP predisposing to type 2 diabetes mellitus, rs10811661 near CDKN2A/B, is associated with diabetic nephropathy in patients with type 1 diabetes mellitus.

A comparison of two informative SNP-based strategies for typing Pseudomonas aeruginosa isolates from patients with cystic fibrosis

BACKGROUND: Molecular typing is integral for identifying Pseudomonas aeruginosa strains that may be shared between patients with cystic fibrosis (CF). We conducted a side-by-side comparison of two P. aeruginosa genotyping methods utilising informative-single nucleotide polymorphism (SNP) methods; one targeting 10 P. aeruginosa SNPs and using real-time polymerase chain reaction technology (HRM10SNP) and the other targeting 20 SNPs and based on the Sequenom MassARRAY platform (iPLEX20SNP).

METHODS: An in-silico analysis of the 20 SNPs used for the iPLEX20SNP method was initially conducted using sequence type (ST) data on the P. aeruginosa PubMLST website. A total of 506 clinical isolates collected from patients attending 11 CF centres throughout Australia were then tested by both the HRM10SNP and iPLEX20SNP assays. Type-ability and discriminatory power of the methods, as well as their ability to identify commonly shared P. aeruginosa strains, were compared.

RESULTS: The in-silico analyses showed that the 1401 STs available on the PubMLST website could be divided into 927 different 20-SNP profiles (D-value = 0.999), and that most STs of national or international importance in CF could be distinguished either individually or as belonging to closely related single- or double-locus variant groups. When applied to the 506 clinical isolates, the iPLEX20SNP provided better discrimination over the HRM10SNP method with 147 different 20-SNP and 92 different 10-SNP profiles observed, respectively. For detecting the three most commonly shared Australian P. aeruginosa strains AUST-01, AUST-02 and AUST-06, the two methods were in agreement for 80/81 (98.8%), 48/49 (97.8%) and 11/12 (91.7%) isolates, respectively.

CONCLUSIONS: The iPLEX20SNP is a superior new method for broader SNP-based MLST-style investigations of P. aeruginosa. However, because of convenience and availability, the HRM10SNP method remains better suited for clinical microbiology laboratories that only utilise real-time PCR technology and where the main interest is detection of the most highly-prevalent P. aeruginosa CF strains within Australian clinics.