Detection and Integration of Genotyping Errors in Statistical Genetics

Detection of genotyping errors and integration of such errors in statistical analysis are relatively neglected topics, given their importance in gene mapping. A few inopportunely placed errors, if ignored, can tremendously affect evidence for linkage. The present study takes a fresh look at the calculation of pedigree likelihoods in the presence of genotyping error. To accommodate genotyping error, we present extensions to the Lander-Green-Kruglyak deterministic algorithm for small pedigrees and to the Markov-chain Monte Carlo stochastic algorithm for large pedigrees. These extensions can accommodate a variety of error models and refrain from simplifying assumptions, such as allowing, at most, one error per pedigree. In principle, almost any statistical genetic analysis can be performed taking errors into account, without actually correcting or deleting suspect genotypes. Three examples illustrate the possibilities. These examples make use of the full pedigree data, multiple linked markers, and a prior error model. The first example is the estimation of genotyping error rates from pedigree data. The second-and currently most useful-example is the computation of posterior mistyping probabilities. These probabilities cover both Mendelian-consistent and Mendelian-inconsistent errors. The third example is the selection of the true pedigree structure connecting a group of people from among several competing pedigree structures. Paternity testing and twin zygosity testing are typical applications.     

Haplotype Inference for Population Data with Genotyping Errors

Inference of haplotypes is important in genetic epidemiology studies. However, all large genotype data sets have errors due to the use of inexpensive genotyping machines that are fallible and shortcomings in genotyping scoring softwares, which can have an enormous impact on haplotype inference. In this article, we propose two novel strategies to reduce the impact induced by genotyping errors in haplotype inference. The first method makes use of double sampling. For each individual, the “GenoSpectrum” that consists of all possible genotypes and their corresponding likelihoods are computed. The second method is a genotype clustering algorithm based on multi‐genotyping data, which also assigns a “GenoSpectrum” for each individual. We then describe two hybrid EM algorithms (called DS‐EM and MG‐EM) that perform haplotype inference based on “GenoSpectrum” of each individual obtained by double sampling and multi‐genotyping data. Both simulated data sets and a quasi real‐data set demonstrate that our proposed methods perform well in different situations and outperform the conventional EM algorithm and the HMM algorithm proposed by Sun, Greenwood, and Neal (2007, Genetic Epidemiology 31 , 937–948) when the genotype data sets have errors.     

A Transmission/Disequilibrium Test That Allows for Genotyping Errors in the Analysis of Single-Nucleotide Polymorphism Data

The present study assesses the effects of genotyping errors on the type I error rate of a particular transmission/disequilibrium test (TDT(std)), which assumes that data are errorless, and introduces a new transmission/disequilibrium test (TDT(ae)) that allows for random genotyping errors. We evaluate the type I error rate and power of the TDT(ae) under a variety of simulations and perform a power comparison between the TDT(std) and the TDT(ae), for errorless data. Both the TDT(std) and the TDT(ae) statistics are computed as two times a log-likelihood difference, and both are asymptotically distributed as chi(2) with 1 df. Genotype data for trios are simulated under a null hypothesis and under an alternative (power) hypothesis. For each simulation, errors are introduced randomly via a computer algorithm with different probabilities (called "allelic error rates"). The TDT(std) statistic is computed on all trios that show Mendelian consistency, whereas the TDT(ae) statistic is computed on all trios. The results indicate that TDT(std) shows a significant increase in type I error when applied to data in which inconsistent trios are removed. This type I error increases both with an increase in sample size and with an increase in the allelic error rates. TDT(ae) always maintains correct type I error rates for the simulations considered. Factors affecting the power of the TDT(ae) are discussed. Finally, the power of TDT(std) is at least that of TDT(ae) for simulations with errorless data. Because data are rarely error free, we recommend that researchers use methods, such as the TDT(ae), that allow for errors in genotype data.     

Survival Probability of Beneficial Mutations in Bacterial Batch Culture

The survival of rare beneficial mutations can be extremely sensitive to the organism’s life history and the trait affected by the mutation. Given the tremendous impact of bacteria in batch culture as a model system for the study of adaptation, it is important to understand the survival probability of beneficial mutations in these populations. Here we develop a life-history model for bacterial populations in batch culture and predict the survival of mutations that increase fitness through their effects on specific traits: lag time, fission time, viability, and the timing of stationary phase. We find that if beneficial mutations are present in the founding population at the beginning of culture growth, mutations that reduce the mortality of daughter cells are the most likely to survive drift. In contrast, of mutations that occur de novo during growth, those that delay the onset of stationary phase are the most likely to survive. Our model predicts that approximately fivefold population growth between bottlenecks will optimize the occurrence and survival of beneficial mutations of all four types. This prediction is relatively insensitive to other model parameters, such as the lag time, fission time, or mortality rate of the population. We further estimate that bottlenecks that are more severe than this optimal prediction substantially reduce the occurrence and survival of adaptive mutations.     

Noninvasive Estimation of Black Bear Abundance Incorporating Genotyping Errors and Harvested Bear

ABSTRACT Estimating black bear (Ursus americanus) population size is a difficult but important requirement when justifying harvest quotas and managing populations. Advancements in genetic techniques provide a means to identify individual bears using DNA contained in tissue and hair samples, thereby permitting estimates of population abundance based on established mark-capture-recapture methodology. We expand on previous noninvasive population-estimation work by geographically extending sampling areas (36,848 km²) to include the entire Northern Lower Peninsula (NLP) of Michigan, USA. We selected sampling locations randomly within biologically relevant bear habitat and used barbed wire hair snares to collect hair samples. Unlike previous noninvasive studies, we used tissue samples from harvested bears as an additional sampling occasion to increase recapture probabilities. We developed subsampling protocols to account for both spatial and temporal variance in sample distribution and variation in sample quality using recently published quality control protocols using 5 microsatellite loci. We quantified genotyping errors using samples from harvested bears and estimated abundance using statistical models that accounted for genotyping error. We estimated the population of yearling and adult black bears in the NLP to be 1,882 bears (95% CI = 1,389-2,551 bears). The derived population estimate with a 15% coefficient of variation was used by wildlife managers to examine the sustainability of harvest over a large geographic area.     

Development and Implementation of a Multiplex Single-Nucleotide Polymorphism Genotyping Assay for Detection of Virulence-Attenuating Mutations in the Listeria monocytogenes Virulence-Associated Gene inlA

The virulence factor internalin A (InlA) facilitates the uptake of Listeria monocytogenes by epithelial cells that express the human isoform of E-cadherin. Previous studies identified naturally occurring premature stop codon (PMSC) mutations in inlA and demonstrated that these mutations are responsible for virulence attenuation. We assembled >1,700 L. monocytogenes isolates from diverse sources representing 90 EcoRI ribotypes. A subset of this isolate collection was selected based on ribotype frequency and characterized by a Caco-2 cell invasion assay. The sequencing of inlA genes from isolates with attenuated invasion capacities revealed three novel inlA PMSCs which had not been identified previously among U.S. isolates. Since ribotypes include isolates with and without inlA PMSCs, we developed a multiplex single-nucleotide polymorphism (SNP) genotyping assay to detect isolates with virulence-attenuating PMSC mutations in inlA. The SNP genotyping assay detects all inlA PMSC mutations that have been reported worldwide and verified in this study to date by the extension of unlabeled primers with fluorescently labeled dideoxynucleoside triphosphates. We implemented the SNP genotyping assay to characterize human clinical and food isolates representing common ribotypes associated with novel inlA PMSC mutations. PMSCs in inlA were significantly (ribotypes DUP-1039C and DUP-1045B; P < 0.001) or marginally (ribotype DUP-1062D; P = 0.11) more common among food isolates than human clinical isolates. SNP genotyping revealed a fourth novel PMSC mutation among U.S. L. monocytogenes isolates, which was observed previously among isolates from France and Portugal. This SNP genotyping assay may be implemented by regulatory agencies and the food industry to differentiate L. monocytogenes isolates carrying virulence-attenuating PMSC mutations in inlA from strains representing the most significant health risk.     

人乳头瘤状病毒分型检测技术研究进展

HPV病毒有100多个亚型,反复持续的高危型人乳头瘤状病毒(Human papillomavirus,HPV)的感染是子宫颈癌发生的必要条件.对其进行分型检测,对子宫颈病变的早期发现和预防有很重要的意义.近年来,HPV分型检测技术发展十分迅速,本文对其相关研究新进展进行综述.     

Point Mutations in Centromeric Histone Induce Post-zygotic Incompatibility and Uniparental Inheritance

The centromeric histone 3 variant (CENH3, aka CENP-A) is essential for the segregation of sister chromatids during mitosis and meiosis. To better define CENH3 functional constraints, we complemented a null allele in Arabidopsis with a variety of mutant alleles, each inducing a single amino acid change in conserved residues of the histone fold domain. Many of these transgenic missense lines displayed wild-type growth and fertility on self-pollination, but exhibited frequent post-zygotic death and uniparental inheritance when crossed with wild-type plants. The failure of centromeres marked by these missense mutation in the histone fold domain of CENH3 reproduces the genome elimination syndromes described with chimeric CENH3 and CENH3 from diverged species. Additionally, evidence that a single point mutation is sufficient to generate a haploid inducer provide a simple one-step method for the identification of non-transgenic haploid inducers in existing mutagenized collections of crop species. As proof of the extreme simplicity of this approach to create haploid-inducing lines, we performed an in silico search for previously identified point mutations in CENH3 and identified an Arabidopsis line carrying the A86V substitution within the histone fold domain. This A87V non-transgenic line, while fully fertile on self-pollination, produced postzygotic death and uniparental haploids when crossed to wild type.     

Assessment of Data Quality: Errors of Measurement and Errors of Process

As projects progress from pilot studies with few simple variables and small samples, the research process as a whole becomes qualitatively more complex and subject to an array of contamination by errors and mistakes. Data usually undergo a series of manipulations (e.g., recording, computer entry, transmission) prior to final statistical analysis. The process, then, consists of numerous operations only ending with eventual statistical analysis and write-up. We present a means of estimating the impact of process error in the same terms as psychometric reliability and discuss the implications for reducing the impact of errors on overall data quality.     

Detection of Mutations in Tumor Suppressor Genes

Defects in vital genes occur in a high percentage of human diseases, including cancer. Defects could be due to the accumulation of mutations in the genes leading to the production of faulty proteins. Although the biological significance of such mutant proteins still remains in question, recent experiments have demonstrated that genes overproducing faulty proteins are often associated with tumor cell growth. Thep53tumor suppressor gene is the most frequently mutated gene yet identified in human cancer. It is mutated in wide variety of human cancers. Missense mutations are common for thep53gene and are essential for the transforming ability of the oncogene. The wild-typep53gene may directly suppress cell growth or indirectly activate genes that are involved in growth suppression. Thus inactivation of wild-typep53by point mutation may contribute to transformation. Therefore, identification of such mutations have potential clinical implications. Recently, polymerase chain reaction-based advanced molecular techniques had a profound impact on the detection and identification of such mutations. These techniques are sensitive and quantitative tools for the study of the pathogenesis of neoplastic diseases at the single-cell level.     

High-Throughput Genotyping in Metastatic Esophageal Squamous Cell Carcinoma Identifies Phosphoinositide-3-Kinase and BRAF Mutations

Background

Given the high incidence of metastatic esophageal squamous cell carcinoma, especially in Asia, we screened for the presence of somatic mutations using OncoMap platform with the aim of defining subsets of patients who may be potential candidate for targeted therapy.

Methods and Materials

We analyzed 87 tissue specimens obtained from 80 patients who were pathologically confirmed with esophageal squamous cell carcinoma and received 5-fluoropyrimidine/platinum-based chemotherapy. OncoMap 4.0, a mass-spectrometry based assay, was used to interrogate 471 oncogenic mutations in 41 commonly mutated genes. Tumor specimens were prepared from primary cancer sites in 70 patients and from metastatic sites in 17 patients. In order to test the concordance between primary and metastatic sites from the patient for mutations, we analyzed 7 paired (primary-metastatic) specimens. All specimens were formalin-fixed paraffin embedded tissues and tumor content was >70%.

Results

In total, we have detected 20 hotspot mutations out of 80 patients screened. The most frequent mutation was PIK3CA mutation (four E545K, five H1047R and one H1047L) (N = 10, 11.5%) followed by MLH1 V384D (N = 7, 8.0%), TP53 (R306, R175H and R273C) (N = 3, 3.5%), BRAF V600E (N = 1, 1.2%), CTNNB1 D32N (N = 1, 1.2%), and EGFR P733L (N = 1, 1.2%). Distributions of somatic mutations were not different according to anatomic sites of esophageal cancer (cervical/upper, mid, lower). In addition, there was no difference in frequency of mutations between primary-metastasis paired samples.

Conclusions

Our study led to the detection of potentially druggable mutations in esophageal SCC which may guide novel therapies in small subsets of esophageal cancer patients.     

基因型错误对数量性状精细定位的哈迪-温伯格不平衡指数的效应

使用紧密相邻的标记位点且与标记基因频率无关的哈迪-温伯格不平衡(HWD)指数被用来对数量性状位点(QTL)进行精细定位.本文讨论了当存在基因型错误时HWD指数的性质.文章指出,当存在基因型错误时,对于在群体的标记基因频率已知的情形使用的两个HWD指数尽管受基因型错误的影响但仍然有效;而仅仅极端样本的标记基因频率已知的情形下使用的两个HWD指数同时与基因型错误和标记基因频率有关.计算机模拟表明,仅仅极端样本的标记基因频率已知的情形下使用的两个HWD指数在精细定位时会产生偏差,不适宜作精细定位.     

First Detection and Genotyping of Human-Associated Microsporidia in Pigeons from Urban Parks

Microsporidia are ubiquitous opportunistic parasites in nature infecting all animal phyla, and the zoonotic potential of this parasitosis is under discussion. Fecal samples from 124 pigeons from seven parks of Murcia (Spain) were analyzed. Thirty-six of them (29.0%) showed structures compatible with microsporidia spores by staining methods. The DNA isolated from 26 fecal samples (20.9%) of microsporidia-positive pigeons was amplified with specific primers for the four most frequent human microsporidia. Twelve pigeons were positive for only Enterocytozoon bieneusi (9.7%), 5 for Encephalitozoon intestinalis (4%), and one for Encephalitozoon hellem (0.8%). Coinfections were detected in eight additional pigeons: E. bieneusi and E. hellem were detected in six animals (4.8%); E. bieneusi was associated with E. intestinalis in one case (0.8%); and E. hellem and E. intestinalis coexisted in one pigeon. No positive samples for Encephalitozoon cuniculi were detected. The internally transcribed spacer genotype could be completed for one E. hellem-positive pigeon; the result was identical to the genotype A1 previously characterized in an E. hellem Spanish strain of human origin. To our knowledge, this is the first time that human-related microsporidia have been identified in urban park pigeons. Moreover, we can conclude that there is no barrier to microsporidia transmission between park pigeons and humans for E. intestinalis and E. hellem. This study is of environmental and sanitary interest, because children and elderly people constitute the main visitors of parks and they are populations at risk for microsporidiosis. It should also contribute to the better design of appropriate prophylactic measures for populations at risk for opportunistic infections.     

从急性腹泻儿童中检出的人博卡病毒2型的研究

为了调查北京地区急性腹泻患儿中人博卡病毒2型（HBoV2）的流行情况并了解这一病毒的基因组特征,本研究收集2010年11月至2011年10月到首都儿科研究所附属儿童医院门诊就诊的急性腹泻患儿的粪便标本553例,采用荧光实时PCR进行HBoV2 DNA的检测。选择2例病毒载量较高的阳性标本进行HBoV2各基因片段的扩增并测序。将所测到的序列进行拼接后得到完整的基因组序列并与GenBank中的相关序列进行比较分析。结果显示,553例粪便标本中共检出HBoV2阳性标本15例,阳性率为2.7%;各年龄组中,3~6月龄患儿中的HBoV2 DNA阳性检出率最高（4.1%）;所检年度中,7月份阳性检出率最高（7.0%）;15例HBoV2检测阳性的患儿年龄均在2岁以下,其中4例患儿同时检出了诺如病毒,3例患儿同时检出了轮状病毒,1例检出了腺病毒。经测序得到两株接近完整的HBoV2基因组序列BJQ19和BJQ390;序列分析表明,这两株序列的同源性为99.2%,与GenBank中的FJ375129同源性最高,分别为99.1%和99.2%,为典型的HBoV2。上述结果表明,北京地区部分儿童的急性腹泻可能与HBoV2感染相关,且HBoV2感染在低年龄组儿童中更为常见。