RPS4Y gene family evolution in primates

Background: The RPS4 gene codifies for ribosomal protein S4, a very well-conserved protein present in all kingdoms. In primates, RPS4 is codified by two functional genes located on both sex chromosomes: the RPS4X and RPS4Y genes. In humans, RPS4Y is duplicated and the Y chromosome therefore carries a third functional paralog: RPS4Y2, which presents a testis-specific expression pattern. Results: DNA sequence analysis of the intronic and cDNA regions of RPS4Y genes from species covering the entire primate phylogeny showed that the duplication event leading to the second Y-linked copy occurred after the divergence of New World monkeys, about 35 million years ago. Maximum likelihood analyses of the synonymous and non-synonymous substitutions revealed that positive selection was acting on RPS4Y2 gene in the human lineage, which represents the first evidence of positive selection on a ribosomal protein gene. Putative positive amino acid replacements affected the three domains of the protein: one of these changes is located in the KOW protein domain and affects the unique invariable position of this motif, and might thus have a dramatic effect on the protein function.Conclusion: Here, we shed new light on the evolutionary history of RPS4Y gene family, especially on that of RPS4Y2. The results point that the RPS4Y1 gene might be maintained to compensate gene dosage between sexes, while RPS4Y2 might have acquired a new function, at least in the lineage leading to humans.

Molecular phylogenetics of soricid shrews (Mammalia) based on mitochondrial cytochrome b gene sequences: with special reference to the Soricinae

Molecular phylogeny of soricid shrews (Soricidae, Eulipotyphla, Mammalia) based on 1140 bp mitochondrial cytochrome b gene (cytb) sequences was inferred by the maximum likelihood (ML) method. All 13 genera of extant Soricinae and two genera of Crocidurinae were included in the analyses. Anourosorex was phylogenetically distant from the main groupings within Soricinae and Crocidurinae in the ML tree. Thus, it could not be determined to which subfamily Anourosorex should be assigned: Soricinae, Crocidurinae or a new subfamily. Soricinae (excluding Anourosorex) should be divided into four tribes: Neomyini, Notiosoricini, Soricini and Blarinini. However, monophyly of Blarinini was not robust in the present data set. Also, branching orders among tribes of Soricinae and those among genera of Neomyini could not be determined because of insufficient phylogenetic information of the cytb sequences. For water shrews of Neomyini (Chimarrogale, Nectogale and Neomys), monophyly of Neomys and the Chimarrogale-Nectogale group could not be verified, which implies the possibility of multiple origins for the semi-aquatic mode of living among taxa within Neomyini. Episoriculus may contain several separate genera. Blarinella was included in Blarinini not Soricini, based on the cytb sequences, but the confidence level was rather low; hence more phylogenetic information is needed to determine its phylogenetic position. Furthermore, some specific problems of taxonomy of soricid shrews were clarified, for example phylogeny of local populations of Notiosorex crawfordi, Chimarrogale himalayica and Crocidura attenuata.

Zonation for 3D aquifer characterization based on joint inversions of multimethod crosshole geophysical data

Predictive groundwater modeling requires accurate information about aquifer characteristics. Geophysical imaging is a powerful tool for delineating aquifer properties at an appropriate scale and resolution, but it suffers from problems of ambiguity. One way to overcome such limitations is to adopt a simultaneous multitechnique inversion strategy. We have developed a methodology for aquifer characterization based on structural joint inversion of multiple geophysical data sets followed by clustering to form zones and subsequent inversion for zonal parameters. Joint inversions based on cross-gradient structural constraints require less restrictive assumptions than, say, applying predefined petro-physical relationships and generally yield superior results. This approach has, for the first time, been applied to three geophysical data types in three dimensions. A classification scheme using maximum likelihood estimation is used to determine the parameters of a Gaussian mixture model that defines zonal geometries from joint-inversion tomograms. The resulting zones are used to estimate representative geophysical parameters of each zone, which are then used for field-scale petrophysical analysis. A synthetic study demonstrated how joint inversion of seismic and radar traveltimes and electrical resistance tomography (ERT) data greatly reduces misclassification of zones (down from 21.3% to 3.7%) and improves the accuracy of retrieved zonal parameters (from 1.8% to 0.3%) compared to individual inversions. We applied our scheme to a data set collected in northeastern Switzerland to delineate lithologic subunits within a gravel aquifer. The inversion models resolve three principal subhorizontal units along with some important 3D heterogeneity. Petro-physical analysis of the zonal parameters indicated approximately 30% variation in porosity within the gravel aquifer and an increasing fraction of finer sediments with depth.

Robust accelerated failure time regression

Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

Phylogenetic relationships and divergence times among dormice (Rodentia, Gliridae) based on three nuclear genes

We examined phylogenetic relationships among six species representing three subfamilies, Glirinae, Graphiurinae and Leithiinae with sequences from three nuclear protein-coding genes (apolipoprotein B, APOB; interphotoreceptor retinoid-binding protein, IRBP; recombination-activating gene 1, RAG1). Phylogenetic trees reconstructed from maximum-parsimony (MP), maximum-likelihood (ML) and Bayesian-inference (BI) analyses showed the monophyly of Glirinae (Glis and Glirulus) and Leithiinae (Dryomys, Eliomys and Muscardinus) with strong support, although the branch length maintaining this relationship was very short, implying rapid diversification among the three subfamilies. Divergence time estimates were calculated from ML (local clock model) and Bayesian-dating method using a calibration point of 25 Myr (million years) ago for the divergence between Glis and Glirulus, and 55 Myr ago for the split between lineages of Gliridae and Sciuridae on the basis of fossil records. The results showed that each lineage of Graphiuros, Glis, Glirulus and Muscardinus dates from the Late Oligocene to the Early Miocene period, which is mostly in agreement with fossil records. Taking into account that warm climate harbouring a glirid-favoured forest dominated from Europe to Asia during this period, it is considered that this warm environment triggered the prosperity of the glirid species through the rapid diversification. Glirulus japonicas is suggested to be a relict of this ancient diversification during the warm period.

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

Heritability of blood pressure in the swiss population: the family-based skipogh study

Objective: Blood pressure is known to aggregate in families. Yet, heritability estimates are population-specific and no Swiss data have been published so far. Moreover, little is known on the heritability of the white-coat effect. We investigated the heritability of various blood pressure (BP) traits in a Swiss population-based sample. Methods: SKIPOGH (Swiss Kidney Project on Genes in Hypertension) is a family-based multi-centre (Lausanne, Bern, Geneva) cross-sectional study that examines the role of genes in determining BP levels. Office and 24-hour ambulatory BP were measured using validated devices (A&D UM-101 and Diasys Integra). We estimated the heritability of systolic BP (SBP), diastolic BP (DBP), heart rate (HR), pulse pressure (PP), proportional white-coat effect (i.e. [office BP-mean ambulatory daytime BP]/mean ambulatory daytime BP), and nocturnal BP dipping (difference between mean ambulatory daytime and night-time BP) using a maximum likelihood method implemented in the SAGE software. Analyses were adjusted for age, sex, body mass index (BMI), and study centre. Analyses involving PP were additionally adjusted for DBP. Results: The 517 men and 579 women included in this analysis had a mean (}SD) age of 46.8 (17.8) and 47.8 (17.1) years and a mean BMI of 26.0 (4.2) and 24.2 (4.6) kg/m2, respectively. Heritability estimates (}SE) for office SBP, DBP, HR, and PP were 0.20}0.07, 0.20}0.07, 0.39}0.08, and 0.16}0.07 (all P<0.01). Heritability estimates for 24-hour ambulatory SBP, DBP, HR, and PP were, respectively, 0.39}0.07, 0.30}.08, 0.19}0.09, and 0.25}0.08 (all P<0.05). The heritability of the white-coat effect was 0.29}0.07 for SBP and 0.31}0.07 for DBP (both P<0.001). The heritability of nocturnal BP dipping was 0.15}0.08 for SBP and 0.22}0.07 for DBP (both P<0.05). Conclusions: We found that the white-coat effect is significantly heritable. Our findings show that BP traits are moderately heritable in a multi-centric study in Switzerland, in line with previous population-based studies, justifying the ongoing search for genetic determinants in this field.

Clustering of HCV coinfections on HIV phylogeny indicates domestic and sexual transmission of HCV.

BACKGROUND: HCV coinfection remains a major cause of morbidity and mortality among HIV-infected individuals and its incidence has increased dramatically in HIV-infected men who have sex with men(MSM). METHODS: Hepatitis C virus (HCV) coinfection in the Swiss HIV Cohort Study(SHCS) was studied by combining clinical data with HIV-1 pol-sequences from the SHCS Drug Resistance Database(DRDB). We inferred maximum-likelihood phylogenetic trees, determined Swiss HIV-transmission pairs as monophyletic patient pairs, and then considered the distribution of HCV on those pairs. RESULTS: Among the 9748 patients in the SHCS-DRDB with known HCV status, 2768(28%) were HCV-positive. Focusing on subtype B(7644 patients), we identified 1555 potential HIV-1 transmission pairs. There, we found that, even after controlling for transmission group, calendar year, age and sex, the odds for an HCV coinfection were increased by an odds ratio (OR) of 3.2 [95% confidence interval (CI) 2.2, 4.7) if a patient clustered with another HCV-positive case. This strong association persisted if transmission groups of intravenous drug users (IDUs), MSMs and heterosexuals (HETs) were considered separately(in all cases OR>2). Finally we found that HCV incidence was increased by a hazard ratio of 2.1 (1.1, 3.8) for individuals paired with an HCV-positive partner. CONCLUSIONS: Patients whose HIV virus is closely related to the HIV virus of HIV/HCV-coinfected patients have a higher risk for carrying or acquiring HCV themselves. This indicates the occurrence of domestic and sexual HCV transmission and allows the identification of patients with a high HCV-infection risk.

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

Quantitative genetic analysis of methylxanthines and phenolic compounds in mate progenies

The objective of this work was to determine the contents of methylxanthines, caffeine and theobromine, and phenolic compounds, chlorogenic and caffeic acids, in 51 mate progenies (half-sib families) and estimate the heritability of genetic parameters. Mate progenies were from five Brazilian municipalities: Pinhão, Ivaí, Barão de Cotegipe, Quedas do Iguaçu, and Cascavel. The progenies were grown in the Ivaí locality. The contents of the compounds were obtained by high performance liquid chromatography (HPLC). The estimation of genetic parameters by the restricted maximum likelihood (REML) and the prediction of genotypic values via best linear unbiased prediction (BLUP) were obtained by the Selegen - REML/BLUP software. Caffeine (0.248-1.663%) and theobromine (0.106-0.807%) contents were significantly different (p<0.05) depending on the region of origin, with high individual heritability (ĥ²>0.5). The two different progeny groups determined for chlorogenic (1.365-2.281%) and caffeic (0.027-0.037%) acid contents were not significantly different (p<0.05) depending on the locality of origin. Individual heritability values were low to medium for chlorogenic (ĥ²<0.4) and caffeic acid (ĥ²<0.3). The content of the compounds and the values of genetic parameters could support breeding programs for mate.

Confirmatory factor analysis of an integrated model of psycopathology assessed with MMPI-2-RF and the MCMI-III

We presented an integrated hierarchical model of psychopathology that more accurately captures empirical patterns of comorbidity between clinical syndromes and personality disorders.In order to verify the structural validity of the model proposed, this study aimed to analyze the convergence between the Restructured Clinical (RC) scales and Personality scales (PSY-5) of the MMPI-2-RF and the Clinical Syndrome and Personality Disorder scales of the MCMI-III.The MMPI-2-RF and MCMI-III were administered to a clinical sample of 377 outpatients (167 men and 210 women).The structural hypothesiswas assessed by using a Confirmatory Factor Analytic design with four common superordinate factors. An independent-cluster-basis solution was proposed based on maximum likelihood estimation and the application of several fit indices.The fit of the proposed model can be considered as good and more so if we take into account its complexity.

Detection and mapping of a lethal locus in a eucalyptus hybrid population

The objective of this work was to verify the existence of a lethal locus in a eucalyptus hybrid population, and to quantify the segregation distortion in the linkage group 3 of the Eucalyptus genome. A E. grandis x E. urophylla hybrid population, which segregates for rust resistance, was genotyped with 19 microsatellite markers belonging to linkage group 3 of the Eucalyptus genome. To quantify the segregation distortion, maximum likelihood (ML) models, specific to outbreeding populations, were used. These models consider the observed marker genotypes and the lethal locus viability as parameters. The ML solutions were obtained using the expectation‑maximization algorithm. A lethal locus in the linkage group 3 was verified and mapped, with high confidence, between the microssatellites EMBRA 189 e EMBRA 122. This lethal locus causes an intense gametic selection from the male side. Its map position is 25 cM from the locus which controls the rust resistance in this population.

Novel method to estimate the phenotypic variation explained by genome-wide association studies reveals large fraction of the missing heritability.

Genome-wide association studies (GWAS) are conducted with the promise to discover novel genetic variants associated with diverse traits. For most traits, associated markers individually explain just a modest fraction of the phenotypic variation, but their number can well be in the hundreds. We developed a maximum likelihood method that allows us to infer the distribution of associated variants even when many of them were missed by chance. Compared to previous approaches, the novelty of our method is that it (a) does not require having an independent (unbiased) estimate of the effect sizes; (b) makes use of the complete distribution of P-values while allowing for the false discovery rate; (c) takes into account allelic heterogeneity and the SNP pruning strategy. We applied our method to the latest GWAS meta-analysis results of the GIANT consortium. It revealed that while the explained variance of genome-wide (GW) significant SNPs is around 1% for waist-hip ratio (WHR), the observed P-values provide evidence for the existence of variants explaining 10% (CI=[8.5-11.5%]) of the phenotypic variance in total. Similarly, the total explained variance likely to exist for height is estimated to be 29% (CI=[28-30%]), three times higher than what the observed GW significant SNPs give rise to. This methodology also enables us to predict the benefit of future GWA studies that aim to reveal more associated genetic markers via increased sample size.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Evidence for adaptive radiation from a phylogenetic study of plant defenses.

One signature of adaptive radiation is a high level of trait change early during the diversification process and a plateau toward the end of the radiation. Although the study of the tempo of evolution has historically been the domain of paleontologists, recently developed phylogenetic tools allow for the rigorous examination of trait evolution in a tremendous diversity of organisms. Enemy-driven adaptive radiation was a key prediction of Ehrlich and Raven's coevolutionary hypothesis [Ehrlich PR, Raven PH (1964) Evolution 18:586-608], yet has remained largely untested. Here we examine patterns of trait evolution in 51 North American milkweed species (Asclepias), using maximum likelihood methods. We study 7 traits of the milkweeds, ranging from seed size and foliar physiological traits to defense traits (cardenolides, latex, and trichomes) previously shown to impact herbivores, including the monarch butterfly. We compare the fit of simple random-walk models of trait evolution to models that incorporate stabilizing selection (Ornstein-Ulenbeck process), as well as time-varying rates of trait evolution. Early bursts of trait evolution were implicated for 2 traits, while stabilizing selection was implicated for several others. We further modeled the relationship between trait change and species diversification while allowing rates of trait evolution to vary during the radiation. Species-rich lineages underwent a proportionately greater decline in latex and cardenolides relative to species-poor lineages, and the rate of trait change was most rapid early in the radiation. An interpretation of this result is that reduced investment in defensive traits accelerated diversification, and disproportionately so, early in the adaptive radiation of milkweeds.