Deciphering the origin of mito‐nuclear discordance in two sibling caddisfly species

An increasing number of phylogenetic studies have reported discordances among nuclear and mitochondrial markers. These discrepancies are highly relevant to widely used biodiversity assessment approaches, such as DNA barcoding, that rely almost exclusively on mitochondrial markers. Although the theoretical causes of mito‐nuclear discordances are well understood, it is often extremely challenging to determine the principal underlying factor in a given study system. In this study, we uncovered significant mito‐nuclear discordances in a pair of sibling caddisfly species. Application of genome sequencing, ddRAD and DNA barcoding revealed ongoing hybridization, as well as historical hybridization in Pleistocene refugia, leading us to identify introgression as the ultimate cause of the observed discordance pattern. Our novel genomic data, the discovery of a European‐wide hybrid zone and the availability of established techniques for laboratory breeding make this species pair an ideal model system for studying species boundaries with ongoing gene flow.     

Specific antibodies in children excreting cytomegalovirus

Acute-and convalescent-phase sera from 22 children were examined by ELISA in comparison with a routine complement fixation (CF) test for detection of anti-CMV antibodies. All these subjects were excreting CMV from urine and/or saliva. The results showed that ELISA is more sensitive than CF test. Particularly ten children showed, by ELISA, anti-CMV antibody titers more agreeing with clinical-virological features. Generally, in other subjects the results of the two serological tests were similar. Three cases showed discordances both between the two methods and between serological data and clinical virological findings.     

Serological Diagnosis of Paracoccidioidomycosis: High Rate of Inter-laboratorial Variability among Medical Mycology Reference Centers

Background

Serological tests have long been established as rapid, simple and inexpensive tools for the diagnosis and follow-up of PCM. However, different protocols and antigen preparations are used and the few attempts to standardize the routine serological methods have not succeeded.

Methodology/Principal findings

We compared the performance of six Brazilian reference centers for serological diagnosis of PCM. Each center provided 30 sera of PCM patients, with positive high, intermediate and low titers, which were defined as the “reference” titers. Each center then applied its own antigen preparation and serological routine test, either semiquantitative double immunodifusion or counterimmmunoelectrophoresis, in the 150 sera from the other five centers blindly as regard to the “reference” titers. Titers were transformed into scores: 0 (negative), 1 (healing titers), 2 (active disease, low titers) and 3 (active disease, high titers) according to each center''s criteria. Major discordances were considered between scores indicating active disease and scores indicating negative or healing titers; such discordance when associated with proper clinical and other laboratorial data, may correspond to different approaches to the patient''s treatment. Surprisingly, all centers exhibited a high rate of “major” discordances with a mean of 31 (20%) discordant scores. Alternatively, when the scores given by one center to their own sera were compared with the scores given to their sera by the remaining five other centers, a high rate of major discordances was also found, with a mean number of 14.8 sera in 30 presenting a discordance with at least one other center. The data also suggest that centers that used CIE and pool of isolates for antigen preparation performed better.

Conclusion

There are inconsistencies among the laboratories that are strong enough to result in conflicting information regarding the patients'' treatment. Renewed efforts should be promoted to improve standardization of the serological diagnosis of PCM.     

Variance Component Estimation for Mixed Model Analysis of cDNA Microarray Data

Microarrays provide a valuable tool for the quantification of gene expression. Usually, however, there is a limited number of replicates leading to unsatisfying variance estimates in a gene‐wise mixed model analysis. As thousands of genes are available, it is desirable to combine information across genes. When more than two tissue types or treatments are to be compared it might be advisable to consider the array effect as random. Then information between arrays may be recovered, which can increase accuracy in estimation. We propose a method of variance component estimation across genes for a linear mixed model with two random effects. The method may be extended to models with more than two random effects. We assume that the variance components follow a log‐normal distribution. Assuming that the sums of squares from the gene‐wise analysis, given the true variance components, follow a scaled χ²‐distribution, we adopt an empirical Bayes approach. The variance components are estimated by the expectation of their posterior distribution. The new method is evaluated in a simulation study. Differentially expressed genes are more likely to be detected by tests based on these variance estimates than by tests based on gene‐wise variance estimates. This effect is most visible in studies with small array numbers. Analyzing a real data set on maize endosperm the method is shown to work well. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

基于转录组测序数据识别黑猩猩RNA编辑位点

使用转录组测序(RNA-Seq)数据识别黑猩猩RNA编辑位点,探索了RNA编辑的识别机制以及潜在的功能影响．基于黑猩猩RNA-Seq数据与基因组序列的比对信息发现RNA-DNA错配位点,并构建编辑位点候选集．从中滤除基因组或转录组测序质量低的位点,其他的过滤条件包括3′端测不准、覆盖度、SNP位点以及估算的编辑水平．构建二项分布统计模型和Bonferroni多重检验滤除候选集中的随机错误,得到RNA编辑位点．选取落在已知基因上的编辑位点进行功能分析,并用Two Sample Logo软件分析编辑位点上下游序列的特征．识别出黑猩猩12种碱基替换型RNA编辑位点8 334个,其中有41个编辑位点改变原有的氨基酸,另有3个编辑位点落在microRNA(miRNA)潜在靶基因的种子结合区．统计学分析表明,分别有640和872个RNA编辑位点存在组织和性别差异．上下游碱基频率分析表明,多种类型的编辑位点紧邻碱基具有显著偏好．结果显示, RNA编辑在黑猩猩体内大量存在,且潜在具有重要的生物学功能,为进一步深入研究灵长类RNA编辑的机制奠定了基础．     

Estimation of genetic parameters of semen characteristics and reproductive traits in AI boars

(Co)variance components and further genetic parameters of boar semen characteristics and reproductive traits were estimated using the REML procedure applied to multi-trait animal models. The calculations were based on data from 210,733 ejaculates stemming from 2862 AI boars and collected from 1990 to 1997 in insemination stations for boars in the Czech Republic. Equal model equations for all traits included the AI station and the breed or breed combination as fixed effects, the interval between two collections for the boar as covariable and the animal and residual effects as random effects. The following heritabilities were estimated: semen volume 0.58, sperm concentration 0.49, progressive motion of spermatozoa 0.38, abnormal spermatozoa 0.34, number of total spermatozoa 0.42, number of insemination doses 0.40, number of piglets born alive 0.08, total number of piglets born 0.05 and conception rate 0.29. Heritabilities and genetic correlations were estimated on average values for each boar.     

Estimating the accuracy of polymerase chain reaction-based tests using endpoint dilution

Polymerase chain reaction (PCR)-based tests for various microorganisms or target DNA sequences are generally acknowledged to be highly "sensitive," yet the concept of sensitivity is ill-defined in the literature on these tests. We propose that sensitivity should be expressed as a function of the number of target DNA molecules in the sample (or specificity, when the target number is 0). However, estimating this "sensitivity curve" is problematic, since it is difficult to construct samples with a fixed number of targets. Nonetheless, using serially diluted replicate aliquots of a known concentration of the target DNA sequence, we show that it is possible to disentangle random variations in the number of target DNA molecules from the underlying test sensitivity. We develop parametric, nonparametric, and semiparametric (spline-based) models for the sensitivity curve. The methods are compared on a new test for M. genitalium.     

A clone-free,single molecule map of the domestic cow (Bos taurus) genome

Background

The cattle (Bos taurus) genome was originally selected for sequencing due to its economic importance and unique biology as a model organism for understanding other ruminants, or mammals. Currently, there are two cattle genome sequence assemblies (UMD3.1 and Btau4.6) from groups using dissimilar assembly algorithms, which were complemented by genetic and physical map resources. However, past comparisons between these assemblies revealed substantial differences. Consequently, such discordances have engendered ambiguities when using reference sequence data, impacting genomic studies in cattle and motivating construction of a new optical map resource--BtOM1.0--to guide comparisons and improvements to the current sequence builds. Accordingly, our comprehensive comparisons of BtOM1.0 against the UMD3.1 and Btau4.6 sequence builds tabulate large-to-immediate scale discordances requiring mediation.

Results

The optical map, BtOM1.0, spanning the B. taurus genome (Hereford breed, L1 Dominette 01449) was assembled from an optical map dataset consisting of 2,973,315 (439 X; raw dataset size before assembly) single molecule optical maps (Rmaps; 1 Rmap = 1 restriction mapped DNA molecule) generated by the Optical Mapping System. The BamHI map spans 2,575.30 Mb and comprises 78 optical contigs assembled by a combination of iterative (using the reference sequence: UMD3.1) and de novo assembly techniques. BtOM1.0 is a high-resolution physical map featuring an average restriction fragment size of 8.91 Kb. Comparisons of BtOM1.0 vs. UMD3.1, or Btau4.6, revealed that Btau4.6 presented far more discordances (7,463) vs. UMD3.1 (4,754). Overall, we found that Btau4.6 presented almost double the number of discordances than UMD3.1 across most of the 6 categories of sequence vs. map discrepancies, which are: COMPLEX (misassembly), DELs (extraneous sequences), INSs (missing sequences), ITs (Inverted/Translocated sequences), ECs (extra restriction cuts) and MCs (missing restriction cuts).

Conclusion

Alignments of UMD3.1 and Btau4.6 to BtOM1.0 reveal discordances commensurate with previous reports, and affirm the NCBI’s current designation of UMD3.1 sequence assembly as the “reference assembly” and the Btau4.6 as the “alternate assembly.” The cattle genome optical map, BtOM1.0, when used as a comprehensive and largely independent guide, will greatly assist improvements to existing sequence builds, and later serve as an accurate physical scaffold for studies concerning the comparative genomics of cattle breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1823-7) contains supplementary material, which is available to authorized users.     

Estimating genetic variance contributed by a quantitative trait locus: A random model approach

Detecting quantitative trait loci (QTL) and estimating QTL variances (represented by the squared QTL effects) are two main goals of QTL mapping and genome-wide association studies (GWAS). However, there are issues associated with estimated QTL variances and such issues have not attracted much attention from the QTL mapping community. Estimated QTL variances are usually biased upwards due to estimation being associated with significance tests. The phenomenon is called the Beavis effect. However, estimated variances of QTL without significance tests can also be biased upwards, which cannot be explained by the Beavis effect; rather, this bias is due to the fact that QTL variances are often estimated as the squares of the estimated QTL effects. The parameters are the QTL effects and the estimated QTL variances are obtained by squaring the estimated QTL effects. This square transformation failed to incorporate the errors of estimated QTL effects into the transformation. The consequence is biases in estimated QTL variances. To correct the biases, we can either reformulate the QTL model by treating the QTL effect as random and directly estimate the QTL variance (as a variance component) or adjust the bias by taking into account the error of the estimated QTL effect. A moment method of estimation has been proposed to correct the bias. The method has been validated via Monte Carlo simulation studies. The method has been applied to QTL mapping for the 10-week-body-weight trait from an F₂ mouse population.     

Tests for character displacement

Character displacement is an important concept in ecology which has been surrounded by controversy due largely to a lack of clearly stated hypotheses and statistical tests. Existing tests implicity assume random species sizes estimated without error--a random-effects model. We introduce the log-uniform distribution for species sizes and show that it has properties of direct relevance to character displacement. We present tests which assume uniform and log-normal species sizes and have the log-uniform distribution as an alternative. The tests have low power for sample sizes typically encountered in ecology. The effect of estimating species sizes is small. The results exemplify the shortcomings of the traditional random-effects model for species sizes.     

Estimation of Fixed and Random Effects in the Functional Nonlinear Errors-in-Variable Model

Consider an experiment where a nonlinear continuous functional relationship exists between y and X. Assume that this relationship has been measured at n replicated points of X from each of t treatments or populations. Assume further that the X are fixed unknown vectors and that the location parameter v is either a fixed unknown vector or a vector of random variables. In the first case various linear hypotheses are to be tested about v, such as tests for main effects and interaction; in the second case, the mean and variance of the random variable v are to be estimated. A two-step procedure based on asymptotic theory is presented to test hypotheses or develop estimates for the fixed effects or random effects functional errors-in-variable model. An example of a one-way random effects model is given.     

Genetic load and viability variation in korean natural populations ofDrosophila melanogaster

Summary Natural populations of Drosophila melanogaster from Anyang and Susac (suburbs of Seoul) have been analyzed with respect to viability variation on the second chromosome. Homozygotes as well as random heterozygotes for wild chromosomes were studied. The frequency of lethal factors was about 16 per cent, that of drastics 26 per cent. The average viability of homozygotes was 0.650 including lethal lines and 0.858 for quasinormals; that for random heterozygotes was 1.125. Allelism tests have been performed for the lethals. The allelism rate turned out to be as high as 0.036 and 0.0214, respectively. Using a formula by Nei, the effective population size can be estimated from these data. Korean D. melanogaster populations proved as small as 2000 to 3000 individuals. No correlation between homozygous and heterozygous viabilities could be found. According to these observations, along with the fact that partly big clusters of identic lethals could be found in the allelism tests, it is concluded that in Korean populations quite a large part of the hard genetic load is balanced. The connection between population size, population structure and associative or genuine overdominance is discussed.     

Expanded Fermi solution for estimating the survival of ingested pathogenic and probiotic microbial cells and spores

The expanded Fermi solution was originally developed for estimating the number of food-poisoning victims when information concerning the circumstances of exposure is scarce. The method has been modified for estimating the initial number of pathogenic or probiotic cells or spores so that enough of them will survive the food preparation and digestive tract's obstacles to reach or colonize the gut in sufficient numbers to have an effect. The method is based on identifying the relevant obstacles and assigning each a survival probability range. The assumed number of needed survivors is also specified as a range. The initial number is then estimated to be the ratio of the number of survivors to the product of the survival probabilities. Assuming that the values of the number of survivors and the survival probabilities are uniformly distributed over their respective ranges, the sought initial number is construed as a random variable with a probability distribution whose parameters are explicitly determined by the individual factors' ranges. The distribution of the initial number is often approximately lognormal, and its mode is taken to be the best estimate of the initial number. The distribution also provides a credible interval for this estimated initial number. The best estimate and credible interval are shown to be robust against small perturbations of the ranges and therefore can help assessors achieve consensus where hard knowledge is scant. The calculation procedure has been automated and made freely downloadable as a Wolfram Demonstration.     

Statistical quality control of variety trial data

I propose detection criteria for identifying an abnormal or erroneous data vector provided by a single variety trial in a longer series of variety trials. The test criteria are based on the linear effects estimated separately for each studied trial using global variance components estimated from the whole series of variety trials. The criteria comprise three mutually independent test statistics. The first one is a quadratic form in the estimated fixed effects, the second one is a quadratic form in the estimated realized linear random effects not including the residual effects, and the third one is a quadratic form in the estimated realized residual effects. Under the null hypothesis defining a valid data vector, the three quadratics have independent chi2 distributions. Under natural alternative hypotheses, they have noncentral chi2 distributions. Decomposing the total variation of the data vector studied into quadratic forms due to different types of the realized linear effects intuitively justifies the resulting test criteria. The decomposition may also be used to show that the resulting tests are likelihood ratio tests. I further present computational procedures that allow us to dispense with the need for prior estimation of the linear effects.     

Estimating Sensitivity of Laboratory Testing for Influenza in Canada through Modelling

Background

The weekly proportion of laboratory tests that are positive for influenza is used in public health surveillance systems to identify periods of influenza activity. We aimed to estimate the sensitivity of influenza testing in Canada based on results of a national respiratory virus surveillance system.

Methods and Findings

The weekly number of influenza-negative tests from 1999 to 2006 was modelled as a function of laboratory-confirmed positive tests for influenza, respiratory syncytial virus (RSV), adenovirus and parainfluenza viruses, seasonality, and trend using Poisson regression. Sensitivity was calculated as the number of influenza positive tests divided by the number of influenza positive tests plus the model-estimated number of false negative tests. The sensitivity of influenza testing was estimated to be 33% (95%CI 32–34%), varying from 30–40% depending on the season and region.

Conclusions

The estimated sensitivity of influenza tests reported to this national laboratory surveillance system is considerably less than reported test characteristics for most laboratory tests. A number of factors may explain this difference, including sample quality and specimen procurement issues as well as test characteristics. Improved diagnosis would permit better estimation of the burden of influenza.     

Fixations of the HIV-1 env gene refute neutralism: New evidence for pan-selective evolution

We examined 103 nucleotide sequences of the HIV-1 env gene, sampled from 35 countries and tested: I) the random (neutral) distribution of the number of nucleotide changes; II) the proportion of bases at molecular equilibrium; III) the neutral expected homogeneity of the distribution of new fixated bases; IV) the hypothesis of the neighbor influence on the mutation rates in a site. The expected random number of fixations per site was estimated by Bose-Einstein statistics, and the expected frequencies of bases by matrices of mutation-fixation rates. The homogeneity of new fixations was analyzed using χ2 and trinomial tests for homogeneity. Fixations of the central base in trinucleotides were used to test the neighbor influence on base substitutions. Neither the number of fixations nor the frequencies of bases fitted the expected neutral distribution. There was a highly significant heterogeneity in the distribution of new fixations, and several sites showed more transversions than transitions, showing that each nucleotide site has its own pattern of change. These three independent results make the neutral theory, the nearly neutral and the neighbor influence hypotheses untenable and indicate that evolution of env is rather highly selective.     

Random Number Sampling Method for Estimation of Lactic Acid Bacteria

A procedure for counting individual organisms or groups with very close cultural characteristics in complex mixtures is described. The method is based upon growth in a medium favourable to all organisms whose enumeration is attempted, selecting 20% of the colonies by the random number sampling method and submitting them to appropriate identification tests.     

Oligonucleotide mapping: evaluation of its sensitivity by computer-simulation.

A frequently used method of comparing large RNA molecules employs the two-dimensional display of oligonucleotides generated through the action of specific RNases (oligonucleotide mapping, fingerprinting). Using computer simulations and simple analytic expressions the number of large RNase T1-resistant oligonucleotides obtained from random RNA sequences can be estimated. The computer simulations also permit estimation of the number of large oligonucleotides which remain unchanged as random variations are introduced into a random RNA sequence. In addition, computer analysis also provides a means of estimating statistical confidence limits to be used in a quantitative comparison of fingerprints of different RNA molecules. The model shows that two RNA sequences which differ overall by 1%, 5% or 10% share, on average, only 85%, 50% or 25%, respectively, of their large oligonucleotides. Thus, the use of fingerprint analysis is recommended only when closely related RNAs or regions of RNAs are compared (sequence homology greater than 90%).     

A random model approach to mapping quantitative trait loci for complex binary traits in outbred populations.

Mapping quantitative trait loci (QTL) for complex binary traits is more challenging than for normally distributed traits due to the nonlinear relationship between the observed phenotype and unobservable genetic effects, especially when the mapping population contains multiple outbred families. Because the number of alleles of a QTL depends on the number of founders in an outbred population, it is more appropriate to treat the effect of each allele as a random variable so that a single variance rather than individual allelic effects is estimated and tested. Such a method is called the random model approach. In this study, we develop the random model approach of QTL mapping for binary traits in outbred populations. An EM-algorithm with a Fisher-scoring algorithm embedded in each E-step is adopted here to estimate the genetic variances. A simple Monte Carlo integration technique is used here to calculate the likelihood-ratio test statistic. For the first time we show that QTL of complex binary traits in an outbred population can be scanned along a chromosome for their positions, estimated for their explained variances, and tested for their statistical significance. Application of the method is illustrated using a set of simulated data.     

Statistical Inference for Hardy-Weinberg Proportions in the Presence of Missing Genotype Information

In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.