All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing

Background

DNA-based methods like PCR efficiently identify and quantify the taxon composition of complex biological materials, but are limited to detecting species targeted by the choice of the primer assay. We show here how untargeted deep sequencing of foodstuff total genomic DNA, followed by bioinformatic analysis of sequence reads, facilitates highly accurate identification of species from all kingdoms of life, at the same time enabling quantitative measurement of the main ingredients and detection of unanticipated food components.

Results

Sequence data simulation and real-case Illumina sequencing of DNA from reference sausages composed of mammalian (pig, cow, horse, sheep) and avian (chicken, turkey) species are able to quantify material correctly at the 1% discrimination level via a read counting approach. An additional metagenomic step facilitates identification of traces from animal, plant and microbial DNA including unexpected species, which is prospectively important for the detection of allergens and pathogens.

Conclusions

Our data suggest that deep sequencing of total genomic DNA from samples of heterogeneous taxon composition promises to be a valuable screening tool for reference species identification and quantification in biosurveillance applications like food testing, potentially alleviating some of the problems in taxon representation and quantification associated with targeted PCR-based approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-639) contains supplementary material, which is available to authorized users.     

X射线损伤修复交叉互补基因1(XRCC1)单核苷酸多态性与神经胶质瘤易感性关系的meta分析(英文)

目的:采用meta分析方法探讨X射线损伤修复交叉互补基因1(XRCC1)单核苷酸多态性与神经胶质瘤易感性的关系。方法:研究检索了PubMed、EMBASE、ISIWeb ofsciences、ScienceDirect及CNKI数据库从建库至2012年9月关于XRCC1基因多态性与神经胶质瘤相关性的相关文献。合并的OR值及其95%CI用于评估不同基因模型与神经胶质瘤风险的关联强度。采用亚组分析和meta回归分析来探索潜在的异质性来源。结果:研究最终纳入12篇Arg399Gln、8篇Arg194Trp和5篇Arg280His XRCC1位点多态性与神经胶质瘤关系文章用于meta分析。Arg399Gln位点多态性在所有基因模型下合并OR值均有显著意义;Arg194Trp位点多态性在纯合子基因模型和隐性基因模型下合并OR值具有显著意义;未发现Arg280His位点多态性与神经胶质瘤风险相关基因模型。亚组分析和meta回归分析显示Arg399Gln位点多态性的所有基因模型风险仅在亚洲人群当中具有显著意义,亚洲人群的风险显著高于白种人群。Arg194Trp对照组人群不符合Hardy-Weinberg平衡(HWE)可能高估了风险。结论:本研究结果显示XRCC1 Arg399Gln基因多态性仅为亚洲人群的神经胶质瘤风险的候选基因,Arg194Trp基因多态性的风险可能是由于对照组不符合HWE的研究所导致的。     

广西仫佬族9个STR的遗传多态性研究

本文采用PCR-STR及基因分型技术,研究广西仫佬族183例无关个体9个STR位点的遗传多态性分布,建立仫佬族群体的遗传学数据库。经统计分析,在9个STR位点共检出70种等位基因,其频率分布在0·0027~0·5301之间;207种基因型,其频率分布在0·0055~0·3388之间;平均杂合度为0·7298,平均多态信息总量为0·7016,累积个体识别力达0·999999999,累积非父排除率达0·999098。与不同民族比较结果显示:广西仫佬族与广西苗、回族及云南、北方各民族之间绝大多数基因座存在显著差异,而与广西壮族和湖南汉族之间绝大多数基因座均无差异。以上数据可为群体遗传学、法医学及人类学等研究提供重要的资料。     

VPOT:A Customizable Variant Prioritization Ordering Tool for Annotated Variants

Next-generation sequencing(NGS) technologies generate thousands to millions of genetic variants per sample.Identification of potential disease-causal variants is labor intensive as it relies on filtering using various annotation metrics and consideration of multiple pathogenicity prediction scores.We have developed VPOT(variant prioritization ordering tool),a python-based command line tool that allows researchers to create a single fully customizable pathogenicity ranking score from any number of annotation values,each with a user-defined weighting.The use of VPOT can be informative when analyzing entire cohorts,as variants in a cohort can be prioritized.VPOT also provides additional functions to allow variant filtering based on a candidate gene list or by affected status in a family pedigree.VPOT outperforms similar tools in terms of efficacy,flexibility,scalability,and computational performance.VPOT is freely available for public use at Git Hub(https://github.com/VCCRI/VPOT/).Documentation for installation along with a user tutorial,a default parameter file,and test data are provided.     

Dissecting High-Dimensional Phenotypes with Bayesian Sparse Factor Analysis of Genetic Covariance Matrices

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism’s entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse – affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.     

用超显性模型估计遗传多态平衡的种群参数

基于超显性模型,采用数学方法阐述了种群遗传多样性的延续机制及平衡条件,从双等位基因导出的定律有较大的局限性,在许多教科书中常用的估计平衡态基因频数的定律只适用于双等位基因,本文用另一种方法导出一些公式,将其扩展到多等位基因,讨论了种群中基因数ｎ,遗传负载荷（Ｌ）,杂合频ＹＸ（Ｈｅ）和纯合频率（Ｈｏｍ）之间的关系。     

Estimation in Bayesian disease mapping

Recent work on Bayesian inference of disease mapping models discusses the advantages of the fully Bayesian (FB) approach over its empirical Bayes (EB) counterpart, suggesting that FB posterior standard deviations of small-area relative risks are more reflective of the uncertainty associated with the relative risk estimation than counterparts based on EB inference, since the latter fail to account for the variability in the estimation of the hyperparameters. In this article, an EB bootstrap methodology for relative risk inference with accurate parametric EB confidence intervals is developed, illustrated, and contrasted with the hyperprior Bayes. We elucidate the close connection between the EB bootstrap methodology and hyperprior Bayes, present a comparison between FB inference via hybrid Markov chain Monte Carlo and EB inference via penalized quasi-likelihood, and illustrate the ability of parametric bootstrap procedures to adjust for the undercoverage in the "naive" EB interval estimates. We discuss the important roles that FB and EB methods play in risk inference, map interpretation, and real-life applications. The work is motivated by a recent analysis of small-area infant mortality rates in the province of British Columbia in Canada.     

E-probe Diagnostic Nucleic acid Analysis (EDNA): A theoretical approach for handling of next generation sequencing data for diagnostics

Plant biosecurity requires rapid identification of pathogenic organisms. While there are many pathogen-specific diagnostic assays, the ability to test for large numbers of pathogens simultaneously is lacking. Next generation sequencing (NGS) allows one to detect all organisms within a given sample, but has computational limitations during assembly and similarity searching of sequence data which extend the time needed to make a diagnostic decision. To minimize the amount of bioinformatic processing time needed, unique pathogen-specific sequences (termed e-probes) were designed to be used in searches of unassembled, non-quality checked, sequence data. E-probes have been designed and tested for several selected phytopathogens, including an RNA virus, a DNA virus, bacteria, fungi, and an oomycete, illustrating the ability to detect several diverse plant pathogens. E-probes of 80 or more nucleotides in length provided satisfactory levels of precision (75%). The number of e-probes designed for each pathogen varied with the genome size of the pathogen. To give confidence to diagnostic calls, a statistical method of determining the presence of a given pathogen was developed, in which target e-probe signals (detection signal) are compared to signals generated by a decoy set of e-probes (background signal). The E-probe Diagnostic Nucleic acid Analysis (EDNA) process provides the framework for a new sequence-based detection system that eliminates the need for assembly of NGS data.     

草地藏系绵羊乳游离氨基酸质量分数及蛋白遗传多态性研究

用反相高效液相色谱法检测草地藏系绵羊乳游离氨基酸质量分数,用聚丙烯酰胺凝胶电泳法研究乳蛋白组分及其遗传多态性。结果表明:草地藏系绵羊乳中检测到17种游离氨基酸,其中质量分数最高的为Arg;与金堂黑山羊乳比较17种游离氨基酸中,甲硫氨酸的质量分数极显著高于金堂黑山羊(p<0.01),而天冬氨酸、甘氨酸、赖氨酸、谷氨酸、苏氨酸、丙氨酸和缬氨酸的质量分数均显著低于金堂黑山羊(p<0.05),其余9种游离氨基酸质量分数未发现明显差异,但两种羊乳中的必需氨基酸总量基本相同,差异不明显(p>0.05)。草地藏系绵羊乳蛋白组分主要包括α-La、β-Lg、CN、IgG等,CN的相对质量分数约50%~52%;研究还发现4种分子量类型的乳上皮粘蛋白MUC1,分子量分别为214kD、209kD、207kD、205kD;CN、β-Lg均未检测到多态性,说明草地藏系绵羊乳蛋白遗传多态性较为贫乏。     

云南汉族酒精依赖综合征与COMT遗传多态性的关联研究

目的：研究儿茶酚胺氧位甲基转移酶（COMT）的不同基因型及等位基因频率在云南汉族酒精依赖综合征患者组和健康对照组的分布差异。方法：应用聚合酶链式反应．限制性片段长度多态性分析法,对COMT基因的rs2075507、rs737865、rs4680、rsl65599四个基因位点进行特异性扩增,限制性内切酶酶切分型。结果：上述4个候选基因中,COMT基因rs737865位点C／C基因型频率在健康对照组较酒依赖组高,其基因型分布在两组中有差异,且具有统计学意义（P〈0．05）。其余3个位点统计学分析均无显著性差异（P〉0．05）。单倍型分析：上述四个候选基因构建出12种主要单倍型（每种单倍型在对照组和酒依赖组中的频率至少有一个大于1％）,单倍型A—C—A—A有可能是云南汉族酒精依赖发生的一种危险因子（OR：2．865,P=0．003347）。连锁不平衡分析显示：云南汉族人群中,COMT基因的rs2075507和rs737865之间存在着强连锁（D〉0．8）。结论：在云南汉族人群中,COMT基因rs2075507、rs4680和rs165599位点与酒依赖无关联性,rs737865C／C基因型可能是酒精依赖的保护因子,可能降低嗜酒的发生率。单倍型A-C-A-A有可能是云南汉族酒精依赖发生的一种危险因子。云南汉族人群中,COMT基因的rs2075507和rs737865之间存在着强连锁。     

云南汉族酒精依赖综合征与COMT遗传多态性的关联研究

目的:研究儿茶酚胺氧位甲基转移酶(COMT)的不同基因型及等位基因频率在云南汉族酒精依赖综合征患者组和健康对照组的分布差异。方法:应用聚合酶链式反应-限制性片段长度多态性分析法,对COMT基因的rs2075507、rs737865、rs4680、rs165599四个基因位点进行特异性扩增,限制性内切酶酶切分型。结果:上述4个候选基因中,COMT基因rs737865位点C/C基因型频率在健康对照组较酒依赖组高,其基因型分布在两组中有差异,且具有统计学意义(P<0.05)其余3个位点统计学分析均无显著性差异(P>0.05)。单倍型分析:上述四个候选基因构建出12种主要单倍型(每种单倍型在对照组和酒依赖组中的频率至少有一个大于1%),单倍型A-C-A-A有可能是云南汉族酒精依赖发生的一种危险因子(OR:2.865,P=0.003347)连锁不平衡分析显示:云南汉族人群中,COMT基因的rs2075507和rs737865之间存在着强连锁(D>0.8)结论:在云南汉族人群中,COMT基因rs2075507、rs4680和rs165599位点与酒依赖无关联性,rs737865C/C基因型可能是酒精依赖的保护因子,可能降低嗜酒的发生率。单倍型A-C-A-A有可能是云南汉族酒精依赖发生的一种危险因子云南汉族人群中,COMT基因的rs2075507和rs737865之间存在着强连锁。     

A Statistical and Comparative Analysis of Genetic Detected by Different Molecular Markers

This paper presented a statistical and comparative analysis of common parameters of plant genetic diversity by using relevant data of 314 wild plant species from 235 published articles. The results indicated that the parameters of genetic diversity revealed by RAPD and AFLP are comparable, but all parameters of genetic variation detected by ISSR, allozyme and SSR are incomparable , which are not comparative with those by RAPD and AFLP. The genetic differentiation value G_st based on Hardy-Weinberg equilibrium is obviously lower than the value Φ_st based on AMOVA analysis, which showed that these two parameters are incomparable as well. Furthermore, the statistical and comparative results of genetic diversity of 179 plant species by RAPD and AFLP indicated that at population level: 1) the genetic diversity of gymnosperm is higher than those of both dicotyledon and monocotyledon of angiosperm, but lower genetic differentiation; 2) the genetic diversity of tree is higher than those of shrub and herb, but lower genetic differentiation; 3) the clonal plant has higher genetic diversity than those reproduce sexnally, and 4) the cross-breeding plant has higher genetic diversity than self- breeding plant; 5 ) the widespread plant species has higher genetic diversity than the rare, endangered or endemic species.     

Segmentation and Estimation for SNP Microarrays: A Bayesian Multiple Change‐Point Approach

Summary High‐density single‐nucleotide polymorphism (SNP) microarrays provide a useful tool for the detection of copy number variants (CNVs). The analysis of such large amounts of data is complicated, especially with regard to determining where copy numbers change and their corresponding values. In this article, we propose a Bayesian multiple change‐point model (BMCP) for segmentation and estimation of SNP microarray data. Segmentation concerns separating a chromosome into regions of equal copy number differences between the sample of interest and some reference, and involves the detection of locations of copy number difference changes. Estimation concerns determining true copy number for each segment. Our approach not only gives posterior estimates for the parameters of interest, namely locations for copy number difference changes and true copy number estimates, but also useful confidence measures. In addition, our algorithm can segment multiple samples simultaneously, and infer both common and rare CNVs across individuals. Finally, for studies of CNVs in tumors, we incorporate an adjustment factor for signal attenuation due to tumor heterogeneity or normal contamination that can improve copy number estimates.     

第Ⅷ凝血因子基因内限制性片段长度多态性(RFLP)的研究及其在甲型血友病基因连锁分析中的应用

本文系统地研究了广东地区汉族人群中FⅧ:C基因内BclⅠ,XbaⅠ和BgⅡ位点RFLP的基因频率。多态性位点BclⅠ,XbaⅠ及BglⅠ的切点阳性率分别为63.5%、43.5%和100%。对Bcll和Xbal多态性切点连锁情况研究显示,19.5%的Bcll切点阳性纯合子为Xbal切点杂合子,证明联合应用此两位点RFLP可以把甲型血友病基因连锁分析的有效率提高到65.9%。用RFLP连锁分析对两例甲型血友病家系中的女性进行了致病基因携带者检测,对另一例家系进行了基因产前诊断。     

Bayesian analysis of censored response data in family‐based genetic association studies

Biomarkers are subject to censoring whenever some measurements are not quantifiable given a laboratory detection limit. Methods for handling censoring have received less attention in genetic epidemiology, and censored data are still often replaced with a fixed value. We compared different strategies for handling a left‐censored continuous biomarker in a family‐based study, where the biomarker is tested for association with a genetic variant, , adjusting for a covariate, X. Allowing different correlations between X and , we compared simple substitution of censored observations with the detection limit followed by a linear mixed effect model (LMM), Bayesian model with noninformative priors, Tobit model with robust standard errors, the multiple imputation (MI) with and without in the imputation followed by a LMM. Our comparison was based on real and simulated data in which 20% and 40% censoring were artificially induced. The complete data were also analyzed with a LMM. In the MICROS study, the Bayesian model gave results closer to those obtained with the complete data. In the simulations, simple substitution was always the most biased method, the Tobit approach gave the least biased estimates at all censoring levels and correlation values, the Bayesian model and both MI approaches gave slightly biased estimates but smaller root mean square errors. On the basis of these results the Bayesian approach is highly recommended for candidate gene studies; however, the computationally simpler Tobit and the MI without are both good options for genome‐wide studies.     

Assessing changes in macrophyte assemblages with salinity in non-riverine wetlands: A Bayesian approach

Bayesian modeling techniques (which accounted for imperfect detection) were used to assess changes in macrophyte assemblages in 58 wetlands along a typical salinity gradient in Western Victoria, Australia. By incorporating detectability into our predictions, an unbiased estimate was made of the relationship between salinity and both individual species occupancy and the expected number of species. When compared to the freshest wetlands, macrophyte species number was predicted to decrease by as much as 60–70% at conductivities of around 6.0 mS cm⁻¹ (11% seawater), a value often considered the upper salinity tolerance for many freshwater aquatic plants. The model also predicted a 40–50% drop in species number at conductivities of around 1.5 mS cm⁻¹ (3% seawater). It was also found that 25 out of 76 freshwater species were unlikely to occur at conductivities above 1.0 mS cm⁻¹. Consequently, secondary salinisation of fresh non-riverine wetlands is highly likely to markedly and negatively impact upon non-riverine wetland macrophyte assemblages.     

玉米穗部性状的多世代联合遗传分析

以玉米自交系095和L26为亲本,通过对P1、P2、F1、F2、B1、B26个基本世代联合分析,研究了秃尖长、穗行数、穗粗、千粒重、穗重、单株产量等穗粒性状的遗传模型。结果表明:穗行数、穗重、单株产量的最适模型为D-2模型,即1对加性主基因+加性-显性多基因混合遗传模型;穗粗、千粒重的最佳模型为B-1模型,符合两对基因加性-显性-上位性模型;秃尖长的最佳模型为E-3,符合两对加性主基因+加性-显性多基因模型。本研究利用主基因与多基因混合遗传模型分析方法对玉米穗部性状进行遗传分析,有助于阐明玉米穗部性状的遗传规律。     

Roles of Genetic Polymorphisms in the Folate Pathway in Childhood Acute Lymphoblastic Leukemia Evaluated by Bayesian Relevance and Effect Size Analysis

In this study we investigated whether polymorphisms in the folate pathway influenced the risk of childhood acute lymphoblastic leukemia (ALL) or the survival rate of the patients. For this we selected and genotyped 67 SNPs in 15 genes in the folate pathway in 543 children with ALL and 529 controls. The results were evaluated by gender adjusted logistic regression and by the Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA) methods. Bayesian structure based odds ratios for the relevant variables and interactions were also calculated. Altogether 9 SNPs in 8 genes were associated with altered susceptibility to ALL. After correction for multiple testing, two associations remained significant. The genotype distribution of the MTHFD1 rs1076991 differed significantly between the ALL and control population. Analyzing the subtypes of the disease the GG genotype increased only the risk of B-cell ALL (p = 3.52×10⁻⁴; OR = 2.00). The GG genotype of the rs3776455 SNP in the MTRR gene was associated with a significantly reduced risk to ALL (p = 1.21×10⁻³; OR = 0.55), which resulted mainly from the reduced risk to B-cell and hyperdiploid-ALL. The TC genotype of the rs9909104 SNP in the SHMT1 gene was associated with a lower survival rate comparing it to the TT genotype (80.2% vs. 88.8%; p = 0.01). The BN-BMLA confirmed the main findings of the frequentist-based analysis and showed structural interactional maps and the probabilities of the different structural association types of the relevant SNPs especially in the hyperdiploid-ALL, involving additional SNPs in genes like TYMS, DHFR and GGH. We also investigated the statistical interactions and redundancies using structural model properties. These results gave further evidence that polymorphisms in the folate pathway could influence the ALL risk and the effectiveness of the therapy. It was also shown that in gene association studies the BN-BMLA could be a useful supplementary to the traditional frequentist-based statistical method.